<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>6052</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Derivatives of Pearson Correlation for Gradient based Analysis of Biomedical Data</title>
    <parentTitle language="eng">Similarity based Clustering, LNCS</parentTitle>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2007p, Author = M. Strickert and F.-M. Schleif and T. Villmann and U. Seiffert, Booktitle = Similarity based Clustering, LNCS, Title = Derivatives of Pearson Correlation for Gradient based Analysis of Biomedical Data, Year = 2007</enrichment>
    <enrichment key="opus.import.dataHash">md5:48d0e2a3b67985b8aabf0bdaf1d8e137</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>M. Strickert</author>
    <author>Frank-Michael Schleif</author>
    <author>T. Villmann</author>
    <author>U. Seiffert</author>
  </doc>
  <doc>
    <id>6054</id>
    <completedYear/>
    <publishedYear>2008</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>129</pageFirst>
    <pageLast>143</pageLast>
    <pageNumber>15</pageNumber>
    <edition/>
    <issue>2</issue>
    <volume>9</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Exploration of Mass-Spectrometric Data in Clinical Proteomics Using Learning Vector Quantization Methods</title>
    <parentTitle language="eng">Briefings in Bioinformatics</parentTitle>
    <enrichment key="opus.import.data">@ARTICLESchleif2008b, Author = T. Villmann and F.-M. Schleif and B. Hammer and M. Kostrzewa, Title = Exploration of Mass-Spectrometric Data in Clinical Proteomics Using Learning Vector Quantization Methods, Volume = 9, Number = 2, Pages = 129–143, journal= Briefings in Bioinformatics, abstract = In the present contribution we present two recently developed classification al- gorithms for analysis of mass-spectrometric data - the supervised neural gas and the fuzzy labeled self-organizing map. The algorithms are inherently regularizing, which is recommended, for these spectral data because of its high dimensionality and the sparseness for specific problems. The algorithms are both prototype based such that the principle of characteristic representants is realized. This leads to an easy interpretation of the generated classifcation model. Further, the fuzzy labeled self-organizing map, is able to process uncertainty in data, and classification results can be obtained as fuzzy decisions. Moreover, this fuzzy classifcation together with the property of topographic mapping offers the possibility of class similarity detec- tion, which can be used for class visualization. We demonstrate the power of both methods for two exemplary examples: the classification of bacteria (listeria types) and neoplastic and non-neoplastic cell populations in breast cancer tissue sections. , Year = 2008</enrichment>
    <enrichment key="opus.import.dataHash">md5:a87d885904667446851e51f8626fea3c</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>T. Villmann</author>
    <author>Frank-Michael Schleif</author>
    <author>B. Hammer</author>
    <author>M. Kostrzewa</author>
  </doc>
  <doc>
    <id>6055</id>
    <completedYear/>
    <publishedYear>2008</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>165</pageFirst>
    <pageLast>168</pageLast>
    <pageNumber>4</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Automatic Identification and Quantification of Metabolites in H-NMR Measurements</title>
    <parentTitle language="eng">In Proceedings of the Workshop on Computational Systems Biology (WCSB) 2008</parentTitle>
    <identifier type="isbn">978-952-15-1988-8</identifier>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2008e, Author = F.-M. Schleif and T. Riemer and M. Cross and T. Villmann, Title = Automatic Identification and Quantification of Metabolites in H-NMR Measurements, Booktitle = In Proceedings of the Workshop on Computational Systems Biology (WCSB) 2008, Pages = 165–168, ISBN = 978-952-15-1988-8, Year = 2008</enrichment>
    <enrichment key="opus.import.dataHash">md5:28384f24dd5ffab1f2a6612134efe80d</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Frank-Michael Schleif</author>
    <author>T. Riemer</author>
    <author>M. Cross</author>
    <author>T. Villmann</author>
  </doc>
  <doc>
    <id>6056</id>
    <completedYear/>
    <publishedYear>2008</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Pattern Recognition by Supervised Relevance Neural Gas and its Application to Spectral Data in Bioinformatics</title>
    <parentTitle language="eng">Encyclopedia of Artificial Intelligence</parentTitle>
    <identifier type="isbn">978-1-59904-849-9</identifier>
    <enrichment key="opus.import.data">@INCOLLECTIONSchleif2008h, Author = F.-M. Schleif and T. Villmann and B. Hammer, Title = Pattern Recognition by Supervised Relevance Neural Gas and its Application to Spectral Data in Bioinformatics, Booktitle = Encyclopedia of Artificial Intelligence, ISBN = 978-1-59904-849-9, Year = 2008</enrichment>
    <enrichment key="opus.import.dataHash">md5:2d9991360c8e160639ad5821024a98a8</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Frank-Michael Schleif</author>
    <author>T. Villmann</author>
    <author>B. Hammer</author>
  </doc>
  <doc>
    <id>6057</id>
    <completedYear/>
    <publishedYear>2008</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>4</pageFirst>
    <pageLast>16</pageLast>
    <pageNumber>13</pageNumber>
    <edition/>
    <issue>1</issue>
    <volume>47</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Prototype based Fuzzy Classification in Clinical Proteomics</title>
    <parentTitle language="eng">International Journal of Approximate Reasoning</parentTitle>
    <enrichment key="opus.import.data">@ARTICLESchleif2008j, Author = F.-M. Schleif and T. Villmann and B. Hammer, Title = Prototype based Fuzzy Classification in Clinical Proteomics, Pages = 4-16, Volume = 47, Number = 1, journal= International Journal of Approximate Reasoning,abstract = Proteomic profiling based on mass spectrometry is an important tool for studies at the protein and peptide level in medicine and health care. Thereby, the identification of relevant masses, which are characteristic for specific sample states e.g. a disease state is complicated. Further, the classification accuracy and safety is especially important in medicine. The determination of classification models for such high dimensional clinical data is a complex task. Specific methods, which are robust with respect to the large number of dimensions and fit to clinical needs, are required. In this contribution two such methods for the construction of nearest prototype classifiers are compared in the context of clinical proteomic studies, which are specifically suited to deal with such high-dimensional functional data. Both methods are suitable to the adaptation of the underling metric, which is useful in proteomic research to get a problem adequate representation of the clinical data. In addition they allow fuzzy classification and for one of them allows fuzzy classified training data. Both algorithms are investigated in detail with respect to their specific properties. A performance analyzes is taken on real clinical proteomic cancer data in a comparative manner. , Year = 2008</enrichment>
    <enrichment key="opus.import.dataHash">md5:5b495d457a49a51110c4d965391b75d5</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Frank-Michael Schleif</author>
    <author>T. Villmann</author>
    <author>B. Hammer</author>
  </doc>
  <doc>
    <id>6058</id>
    <completedYear/>
    <publishedYear>2009</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>189</pageFirst>
    <pageLast>199</pageLast>
    <pageNumber>11</pageNumber>
    <edition/>
    <issue/>
    <volume>12</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Support Vector Classification of Proteomic Profile Spectra based on Feature Extraction with the Bi-orthogonal Discrete Wavelet Transform</title>
    <parentTitle language="eng">Computing and Visualization in Science</parentTitle>
    <enrichment key="opus.import.data">@ARTICLESchleif2009a, Author = F.-M. Schleif and M. Lindemann and P. Maass and M. Diaz and J. Decker and T. Elssner and M. Kuhn and H. Thiele, Title = Support Vector Classification of Proteomic Profile Spectra based on Feature Extraction with the Bi-orthogonal Discrete Wavelet Transform, Pages = 189–199, Volume = 12, journal= Computing and Visualization in Science,abstract = Automatic classification of high-resolution mass spectrometry data has increasing potential to support physicians in diagnosis of diseases like cancer. The proteomic data exhibit variations among different disease states. A precise and reliable classification of mass spectra is essential for a successful diagnosis and treat- ment. The underlying process to obtain such reliable classification results is a crucial point. In this paper such a method is explained and a corresponding semi automatic parametrization procedure is derived. Thereby a simple straightforward classification procedure to assign mass spectra to a particular disease state is derived. The method is based on an initial preprocessing stage of the whole set of spectra followed by the bi-orthogonal discrete wavelet transform (DWT) for feature extraction. The approximation coefficients calculated from the scaling function exhibit a high peak pattern matching property and feature a denoising of the spectrum. The discriminating coefficients, selected by the Kolmogorov- Smirnov test are finally used as features for training and testing a support vector machine with both a linear and a radial basis kernel. For comparison the peak areas obtained with the ClinProt-System1 [33] were analyzed using the same support vector machines. The introduced approach was evaluated on clinical MALDI-MS data sets with two classes each originating from cancer studies. The cross validated error rates using the wavelet coeffi- cients where better than those obtained from the peak areas. , Year = 2009</enrichment>
    <enrichment key="opus.import.dataHash">md5:2e5c61b6c6364b69d7f4de46460e67fd</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Frank-Michael Schleif</author>
    <author>M. Lindemann</author>
    <author>P. Maass</author>
    <author>M. Diaz</author>
    <author>J. Decker</author>
    <author>T. Elssner</author>
    <author>M. Kuhn</author>
    <author>H. Thiele</author>
  </doc>
  <doc>
    <id>6059</id>
    <completedYear/>
    <publishedYear>2010</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>103</pageFirst>
    <pageLast>106</pageLast>
    <pageNumber>4</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Hierarchical evolving trees together with global and local learning for large data sets in MALDI imaging</title>
    <parentTitle language="eng">Proceedings of WCSB 2010</parentTitle>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2010j, Author = S. Simmuteit and F.-M. Schleif and T. Villmann, Title = Hierarchical evolving trees together with global and local learning for large data sets in MALDI imaging, Booktitle = Proceedings of WCSB 2010, Pages = 103–106, Year = 2010,abstract = The analysis of very large sets of data with multiple thousand measurements is an increasing problem. High- throughput approaches in the life science lead to large amounts of data which need to be analyzed by data mining approaches. Focusing on clustering and visualization approaches a common problem are very large similarity matrices. Standard techniques suffer from memory and runtime limitations for such complex settings or are not applicable at all. Here we present a hierarchical composite clustering employing data specific properties to deal with this problem for data with an inherent hierarchical order. As an additional advantage our algorithm allows easy control of the clustering depth. The method is a prototype based approach leading to sparse, compact and interpretable models. We derive the algorithm and present it on data taken from tissues slices of high resolution MALDI Imaging. Results show an effective clustering as well as significant improvements of the computational complexity for this type of data.</enrichment>
    <enrichment key="opus.import.dataHash">md5:b8f6a21223f0677f05e9a85015911318</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>S. Simmuteit</author>
    <author>Frank-Michael Schleif</author>
    <author>T. Villmann</author>
  </doc>
  <doc>
    <id>6060</id>
    <completedYear/>
    <publishedYear>2010</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>91</pageFirst>
    <pageLast>94</pageLast>
    <pageNumber>4</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Efficient identification and quantification of metabolites in 1-H NMR measurements by a novel data encoding approach</title>
    <parentTitle language="eng">Proceedings of WCSB 2010</parentTitle>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2010k, Author = F.-M. Schleif and T. Riemer and U. Boerner and L. Schnapka-Hille and M. Cross, Title = Efficient identification and quantification of metabolites in 1-H NMR measurements by a novel data encoding approach , Booktitle = Proceedings of WCSB 2010, Pages = 91–94, Year = 2010,abstract = The analysis of metabolic processes is becoming increasingly important to our understanding of complex biological systems and disease states. Nuclear magnetic resonance (NMR) spectroscopy is a particularly relevant technology in this respect, since the NMR signals provide a quantitative measure of metabolite concentrations. How- ever, due to the complexity of the spectra typical of bio- logical samples, the demands of clinical and high through- put analysis will only be fully met by a system capable of reliable, automatic processing of the spectra. We present here a novel data representation strategy for the measured spectra which simplifies the pre-processing of the data and supports the automatic identication and quantification of metabolites. The approach is combined with an extended targeted profiling strategy to allow the highly automated processing of 1 H NMR spectra, generating readouts suitable for the derivation of system biological models. The parallel application of both manual expert analysis and the automated approach to 1 H NMR spectra obtained from stem cell extracts shows that the results obtained are highly comparable. Use of the automated system therefore significantly reduces the effort normally associated with manual processing and paves the way for reliable, high throughput analysis of complex NMR spectra.</enrichment>
    <enrichment key="opus.import.dataHash">md5:0e697b25c4fad14014d305ed566919d0</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Frank-Michael Schleif</author>
    <author>T. Riemer</author>
    <author>U. Boerner</author>
    <author>L. Schnapka-Hille</author>
    <author>M. Cross</author>
  </doc>
  <doc>
    <id>6061</id>
    <completedYear/>
    <publishedYear>2011</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>CD</pageFirst>
    <pageLast>publication</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Hierarchical deconvolution of linear mixtures of high-dimensional mass spectra in micro-biology</title>
    <parentTitle language="eng">Proceedings of AIA 2011</parentTitle>
    <identifier type="doi">http://dx.doi.org/10.2316/P.2011.717-011</identifier>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2011a, Author = F.-M. Schleif and S. Simmuteit and T. Villmann, Title = Hierarchical deconvolution of linear mixtures of high-dimensional mass spectra in micro-biology, Booktitle = Proceedings of AIA 2011, Pages = CD-publication, DOI = http://dx.doi.org/10.2316/P.2011.717-011, Year = 2011,abstract = This paper introduces a hierarchical model for the description and deconvolution of composite patterns. The patterns are described in a basis system of spectral basis functions. The mixture coefficients for the composite patterns are determined by solving a linear mixture model with nonneg- ative coefficients. In life science research, wet-lab mixed samples of possible known basis substances occur regularly and cause a challenge for identification tasks. Also in case of known basis functions the problem is still complex, if the used basis is very sparse and the number of basis functions is very large. Simple approaches either try combining different basis spectra or incorporate blind source separation. Our proposed method is to use nonnegative least squares combined with a hierarchical prototype based learning model. We evaluate our method on mixtures of real and simulated composite patterns of mass spectrometry data from bacteria. Results show remarkable success and can be taken as a promising step in the new field of automatic unmixing of mixed cultures.</enrichment>
    <enrichment key="opus.import.dataHash">md5:082b3971c5d97b46b5f80f0e81c4b642</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Frank-Michael Schleif</author>
    <author>S. Simmuteit</author>
    <author>T. Villmann</author>
  </doc>
  <doc>
    <id>6042</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1036</pageFirst>
    <pageLast>1044</pageLast>
    <pageNumber>9</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Supervised Neural Gas for Functional Data and its Application to the Analysis of Clinical Proteom Spectra</title>
    <parentTitle language="eng">In Proceedings of the 9th International Work-Conference on Artificial Neural Networks (IWANN) 2007</parentTitle>
    <identifier type="isbn">978-3-540-73006-4</identifier>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2007b, Author = F.-M. Schleif and B. Hammer and Th. Villmann, Booktitle = In Proceedings of the 9th International Work-Conference on Artificial Neural Networks (IWANN) 2007, Editors = Francisco Sandoval and Alberto Prieto and Joan Cabestany and Manuel Grana, Publisher = Springer, Address = Berlin, Heidelberg, Germany, Pages = 1036–1044, Title = Supervised Neural Gas for Functional Data and its Application to the Analysis of Clinical Proteom Spectra, ISBN = 978-3-540-73006-4, Year = 2007</enrichment>
    <enrichment key="opus.import.dataHash">md5:978c4a7bbff5cd465125578afd8c96b0</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Frank-Michael Schleif</author>
    <author>B. Hammer</author>
    <author>Th. Villmann</author>
  </doc>
  <doc>
    <id>6043</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>539</pageFirst>
    <pageLast>546</pageLast>
    <pageNumber>8</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Neural gas clustering for sparse proximity data</title>
    <parentTitle language="eng">In Proceedings of the 9th International Work-Conference on Artificial Neural Networks (IWANN) 2007</parentTitle>
    <identifier type="isbn">978-3-540-73006-4</identifier>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2007d, Author = A. Hasenfuss and B. Hammer and F.-M. Schleif and T. Villmann, Booktitle = In Proceedings of the 9th International Work-Conference on Artificial Neural Networks (IWANN) 2007, Editors = Francisco Sandoval and Alberto Prieto and Joan Cabestany and Manuel Grana, Publisher = Springer, Address = Berlin, Heidelberg, Germany, Pages = 539–546, Title = Neural gas clustering for sparse proximity data, ISBN = 978-3-540-73006-4, Year = 2007</enrichment>
    <enrichment key="opus.import.dataHash">md5:5068dd9f9512867b3af04770082bd28e</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>A. Hasenfuss</author>
    <author>B. Hammer</author>
    <author>Frank-Michael Schleif</author>
    <author> T. Villmann</author>
  </doc>
  <doc>
    <id>6044</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>403</pageFirst>
    <pageLast>405</pageLast>
    <pageNumber>3</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Statistical Classification and Visualization of MALDI-Imaging Data</title>
    <parentTitle language="eng">Proc. of CBMS 2007</parentTitle>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2007g, Author = S.-O. Deininger and M. Gerhard and F.-M. Schleif, Booktitle = Proc. of CBMS 2007, Pages = 403–405, Title = Statistical Classification and Visualization of MALDI-Imaging Data, Year = 2007</enrichment>
    <enrichment key="opus.import.dataHash">md5:7e6b26bb189887bf3a4cbd14af00edc7</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>S.-O. Deininger</author>
    <author>M. Gerhard</author>
    <author>Frank-Michael Schleif</author>
  </doc>
  <doc>
    <id>6045</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>179</pageFirst>
    <pageLast>188</pageLast>
    <pageNumber>10</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Prototypen basiertes maschinelles Lernen in der klinische Proteomik</title>
    <parentTitle language="eng">Ausgezeichnete Informatikdissertationen 2006</parentTitle>
    <identifier type="isbn">978-3-88579-411-0</identifier>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2007i, Author = F.-M. Schleif, Booktitle = Ausgezeichnete Informatikdissertationen 2006, Pages = 179–188, Title = Prototypen basiertes maschinelles Lernen in der klinische Proteomik, Publisher = GI-Edition Lecture Notes in Informatics (LNI), ISBN = 978-3-88579-411-0, Year = 2007</enrichment>
    <enrichment key="opus.import.dataHash">md5:fd12c4c62e21faaa22191f96bdecf508</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Frank-Michael Schleif</author>
  </doc>
  <doc>
    <id>6046</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>http://biecoll.ub.uni</pageFirst>
    <pageLast>bielefeld.de//frontdoor.php?source_opus=128&amp;la=en</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Class imaging of hyperspectral satellite remote sensing data using Fuzzy labeled Self Organizing Maps</title>
    <parentTitle language="eng">Proc. of WSOM 2007</parentTitle>
    <identifier type="isbn">9783000224</identifier>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2007j, Author = T. Villmann and F.-M. Schleif and B. Hammer and M. Strickert and E. Merenyi, Booktitle = Proc. of WSOM 2007, Pages = http://biecoll.ub.uni-bielefeld.de//frontdoor.php?source_opus=128&amp;la=en, Title = Class imaging of hyperspectral satellite remote sensing data using Fuzzy labeled Self Organizing Maps, Publisher = Bielefeld University Press, ISBN = 9783000224, Year = 2007</enrichment>
    <enrichment key="opus.import.dataHash">md5:40e1db04a8c6df20d14b1dce2f2a0b15</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>T. Villmann</author>
    <author>Frank-Michael Schleif</author>
    <author>B. Hammer</author>
    <author>M. Strickert</author>
    <author>E. Merenyi</author>
  </doc>
  <doc>
    <id>6047</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>http://biecoll.ub.uni</pageFirst>
    <pageLast>bielefeld.de//frontdoor.php?source_opus=125&amp;la=en</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Advanced metric adaptation in General LVQ for classification of mass spectrometry data</title>
    <parentTitle language="eng">Proc. of WSOM 2007</parentTitle>
    <identifier type="isbn">9783000224</identifier>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2007k, Author = P. Schneider and M. Biehl and F.-M. Schleif and B. Hammer, Booktitle = Proc. of WSOM 2007, Pages = http://biecoll.ub.uni-bielefeld.de//frontdoor.php?source_opus=125&amp;la=en, Title = Advanced metric adaptation in General LVQ for classification of mass spectrometry data, Publisher = Bielefeld University Press, ISBN = 9783000224, Year = 2007</enrichment>
    <enrichment key="opus.import.dataHash">md5:cf5df50eb47424bbfcac27546b06f174</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>P. Schneider</author>
    <author>M. Biehl</author>
    <author>Frank-Michael Schleif</author>
    <author>B. Hammer</author>
  </doc>
  <doc>
    <id>6048</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>139</pageFirst>
    <pageLast>150</pageLast>
    <pageNumber>12</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Gradients of Pearson Correlation for Analysis of Biomedical Data</title>
    <parentTitle language="eng">Proc. of ASAI 2007</parentTitle>
    <identifier type="isbn">18502784</identifier>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2007l, Author = M. Strickert and F.-M. Schleif and U. Seiffert, Booktitle = Proc. of ASAI 2007, Pages = 139–150, Title = Gradients of Pearson Correlation for Analysis of Biomedical Data, ISBN = 18502784, Year = 2007</enrichment>
    <enrichment key="opus.import.dataHash">md5:9f95d073e470d7821232fdee2a016ea3</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>M. Strickert</author>
    <author>Frank-Michael Schleif</author>
    <author>U. Seiffert</author>
  </doc>
  <doc>
    <id>6049</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>81</pageFirst>
    <pageLast>86</pageLast>
    <pageNumber>6</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Supervised Attribute Relevance Determination for Protein Identification in Stress Experiments</title>
    <parentTitle language="eng">Proc. of MLSB 2007</parentTitle>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2007m, Author = M. Strickert and F.-M. Schleif, Booktitle = Proc. of MLSB 2007, Pages = 81–86, Title = Supervised Attribute Relevance Determination for Protein Identification in Stress Experiments, Year = 2007</enrichment>
    <enrichment key="opus.import.dataHash">md5:f321ae87e39cb00fa58b192cb5f7254c</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>M. Strickert</author>
    <author>Frank-Michael Schleif</author>
  </doc>
  <doc>
    <id>6050</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>581</pageFirst>
    <pageLast>586</pageLast>
    <pageNumber>6</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Associative learning in SOMs for Fuzzy-Classification</title>
    <parentTitle language="eng">Proc. of ICMLA 2007</parentTitle>
    <identifier type="isbn">0-7695-3069-9</identifier>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2007n, Author = T. Villmann and F.-M. Schleif and M. v.d.Werff and A. Deelder and R. Tollenaar, Booktitle = Proc. of ICMLA 2007, Pages = 581–586, Title = Associative learning in SOMs for Fuzzy-Classification, ISBN = 0-7695-3069-9, Year = 2007</enrichment>
    <enrichment key="opus.import.dataHash">md5:fafd113d2861023126718e2c67804b08</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>T. Villmann</author>
    <author>Frank-Michael Schleif</author>
    <author>M. v.d. Werff</author>
    <author>A. Deelder</author>
    <author>R. Tollenaar</author>
  </doc>
  <doc>
    <id>6051</id>
    <completedYear/>
    <publishedYear>2007</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>65</pageFirst>
    <pageLast>67</pageLast>
    <pageNumber>3</pageNumber>
    <edition/>
    <issue/>
    <volume>4/07</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Maschinelles Lernen mit Prototypmethoden in der klinischen Proteomik</title>
    <parentTitle language="eng">Künstliche Intelligenz (KI)</parentTitle>
    <identifier type="isbn">0933-1875</identifier>
    <enrichment key="opus.import.data">@ARTICLESchleif2007o, Author = F.-M. Schleif, Title = Maschinelles Lernen mit Prototypmethoden in der klinischen Proteomik, Pages = 65–67, Volume = 4/07, journal = Künstliche Intelligenz (KI), abstract = Die klinische Proteomik untersucht proteinbasierte Krankheitsprozesse in klinischen Proben. Die Messung der Probe erfolgt dabei typischer Weise durch ein Massenspektrometer. Dabei entstehen hochdimensionale Spektren, die die Expressivität von bestimmten Proteinfragmenten anzeigen. Eine weitere Herausforderung ist die eher geringe Anzahl von Proben. Zudem ist die Güte und Interpretierbarkeit der Klassifikationsentscheidung von besonderer Bedeutung und die Adaptierbarkeit der generischen Klassifikationsmodelle bei Nachmessungen. Entsprechend werden die Spektren zur Weiterverarbeitung geeignet reduziert. Nach geeigneter Evaluierung, können diese für die Analyse und Diagnostik von Krankheitsprozessen in Frage kommen. Wir betrachten kurz die Aufbereitung der Spektren, nachfolgend werden Konzepte prototypischer Klassifikationsverfahren beschrieben und deren Erweiterungen f ̈r die klinische Proteomik skizziert. Im Ergebnisteil wird die entwickelte Algorithmik zur Bildung von Klassifikationsmodellen für verschiedene klinische Datensätze eingesetzt und bewertet. , ISBN = 0933-1875, Year = 2007</enrichment>
    <enrichment key="opus.import.dataHash">md5:23b3456268a955e743f54426dceda786</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Frank-Michael Schleif</author>
  </doc>
  <doc>
    <id>6032</id>
    <completedYear/>
    <publishedYear>2002</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>masterthesis</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Momentbasierte Methoden zur Schriftzeichenerkennung</title>
    <enrichment key="opus.import.data">@mastersthesisSchleif2002b, author = F.-M. Schleif, title = Momentbasierte Methoden zur Schriftzeichenerkennung, year = 2002, school = University of Leipzig, publisher = University of Leipzig, address = Dokumentenserver Universität Leipzig, http://dol.uni-leipzig.de/pub/2002-33</enrichment>
    <enrichment key="opus.import.dataHash">md5:ebc1fc978b4427eb57262e490e953799</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Frank-Michael Schleif</author>
  </doc>
  <doc>
    <id>6033</id>
    <completedYear/>
    <publishedYear>2003</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>47</pageFirst>
    <pageLast>52</pageLast>
    <pageNumber>6</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Supervised Neural Gas and Relevance Learning in Learning Vector Quantisation</title>
    <parentTitle language="eng">In Proceedings of the 4th Workshop on Self Organizing Maps (WSOM) 2003</parentTitle>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2003a, Author = Th. Villmann and F.-M. Schleif and B. Hammer, Booktitle = In Proceedings of the 4th Workshop on Self Organizing Maps (WSOM) 2003, Pages = 47–52, Title = Supervised Neural Gas and Relevance Learning in Learning Vector Quantisation, Editor = Takeshi Yamakawa, Publisher = Kyushu Institute of Technology on CD-ROM (C) 2003 WSOM’03 Organizing Committee, Address = Hibikino, Kitakyushu, Japan, Year = 2003</enrichment>
    <enrichment key="opus.import.dataHash">md5:bed8b6fe71e419fbdd36e4eeda0e3dba</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Th. Villmann</author>
    <author>Frank-Michael Schleif</author>
    <author>B. Hammer</author>
  </doc>
  <doc>
    <id>6034</id>
    <completedYear/>
    <publishedYear>2003</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>705</pageFirst>
    <pageLast>713</pageLast>
    <pageNumber>9</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A distributed logistic support communication system</title>
    <parentTitle language="eng">In Proceedings of ISD 2003 - Constructing the Infrastructure for the Knowledge Economy - Methods and Tools, Theory and Practice</parentTitle>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2003b, Author = V. Gruhn and M. Hülder and R. Ijoui and F.-M. Schleif, Booktitle = In Proceedings of ISD 2003 - Constructing the Infrastructure for the Knowledge Economy - Methods and Tools, Theory and Practice, Pages = 705–713, Title = A distributed logistic support communication system, Editor = H. Linger and J. Fisher and W.G. Wojtkowski and J. Zupancic and K. Vigo and J. Arnold, Publisher = Kluwer Academic Publishers, London, Year = 2003</enrichment>
    <enrichment key="opus.import.dataHash">md5:76d76ee7b670b829e5cf1a5125647a95</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>V. Gruhn</author>
    <author>M. Hülder</author>
    <author>R. Ijoui</author>
    <author>Frank-Michael Schleif</author>
  </doc>
  <doc>
    <id>6035</id>
    <completedYear/>
    <publishedYear>2003</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>269</pageFirst>
    <pageLast>269</pageLast>
    <pageNumber>1</pageNumber>
    <edition/>
    <issue>4</issue>
    <volume>15</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Working memory load and EEG coherence</title>
    <parentTitle language="eng">Brain Topography</parentTitle>
    <identifier type="isbn">ISSN 0896-0267</identifier>
    <enrichment key="opus.import.data">@ARTICLESchleif2003c, Author = T. Dörfler and A. Simmel and F.-M. Schleif and E. Sommerfeld, Title = Working memory load and EEG coherence, Pages = 269, Volume = 15, Number = 4, ISBN = ISSN 0896-0267, journal= Brain Topography, Year = 2003</enrichment>
    <enrichment key="opus.import.dataHash">md5:1305cd4103467c5325a5b20654243613</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>T. Dörfler</author>
    <author>A. Simmel</author>
    <author>Frank-Michael Schleif</author>
    <author>E. Sommerfeld</author>
  </doc>
  <doc>
    <id>6036</id>
    <completedYear/>
    <publishedYear>2003</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>271</pageFirst>
    <pageLast>271</pageLast>
    <pageNumber>1</pageNumber>
    <edition/>
    <issue>4</issue>
    <volume>15</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A mission for the EEG coherence analysis: Is the task complex or difficult?</title>
    <parentTitle language="eng">Brain Topography</parentTitle>
    <identifier type="isbn">ISSN 0896-0267</identifier>
    <enrichment key="opus.import.data">@ARTICLESchleif2003d, Author = M. Köhler and K. Buchta and F.-M. and F.-M. Schleif and E. Sommerfeld, Title = A mission for the EEG coherence analysis: Is the task complex or difficult?, Pages = 271, Volume = 15, Number = 4, ISBN = ISSN 0896-0267, journal= Brain Topography, Year = 2003</enrichment>
    <enrichment key="opus.import.dataHash">md5:3b039c895940a51e8d563ebae937f32b</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>M. Köhler</author>
    <author>K. Buchta</author>
    <author> F.-M.</author>
    <author>Frank-Michael Schleif</author>
    <author>E. Sommerfeld</author>
  </doc>
  <doc>
    <id>6037</id>
    <completedYear/>
    <publishedYear>2004</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>592</pageFirst>
    <pageLast>597</pageLast>
    <pageNumber>6</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Metrik Adaptation for Optimal Feature Classification in Learning Vector Quantization Applied to Environment Detection</title>
    <parentTitle language="eng">In Proceedings of Selbstorganisation Von Adaptivem Verfahren (SOAVE’2004)</parentTitle>
    <identifier type="isbn">3-18-374310-8</identifier>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2004a, Author = T. Villmann and B. Hammer and F.-M. Schleif, Booktitle = In Proceedings of Selbstorganisation Von Adaptivem Verfahren (SOAVE’2004), Pages = 592–597, Editors = H.-M. Groß and K. Debes and H.-J. Böhme, ISBN = 3-18-374310-8, Title = Metrik Adaptation for Optimal Feature Classification in Learning Vector Quantization Applied to Environment Detection, Publisher = Fortschritts-Berichte VDI Reihe 10, Nr. 742, VDI Verlag, Germany, Year = 2004</enrichment>
    <enrichment key="opus.import.dataHash">md5:25bd050c5f07010ea7dce45e61947ce3</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>T. Villmann</author>
    <author>B. Hammer</author>
    <author>Frank-Michael Schleif</author>
  </doc>
  <doc>
    <id>6038</id>
    <completedYear/>
    <publishedYear>2005</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>283</pageFirst>
    <pageLast>290</pageLast>
    <pageNumber>8</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Fuzzy Labeled Neural GAS for Fuzzy Classification</title>
    <parentTitle language="eng">Proceedings of the 5th Workshop on Self-Organizing Maps (WSOM) 2005</parentTitle>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2005b, Author = Th. Villmann and B. Hammer and F.-M. Schleif and T. Geweniger, Title = Fuzzy Labeled Neural GAS for Fuzzy Classification, Booktitle = Proceedings of the 5th Workshop on Self-Organizing Maps (WSOM) 2005, Pages = 283–290, Editor = Marie Cottrell, Publisher = University Paris-1-Pantheon-Sorbonne on CD-ROM (C) 2005 WSOM’05 Organizing Committee, Address = Paris, France, Year = 2005</enrichment>
    <enrichment key="opus.import.dataHash">md5:31a0825beafc36eba9ba73f62b775d12</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Th. Villmann</author>
    <author>B. Hammer</author>
    <author>Frank-Michael Schleif</author>
    <author>T. Geweniger</author>
  </doc>
  <doc>
    <id>6039</id>
    <completedYear/>
    <publishedYear>2006</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>623</pageFirst>
    <pageLast>632</pageLast>
    <pageNumber>10</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Supervised median clustering</title>
    <parentTitle language="eng">Proc. of ANNIE 2006</parentTitle>
    <identifier type="isbn">0-7918-0256-6</identifier>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2006i, Author = B. Hammer and A. Hasenfuss and F.-M. Schleif and T. Villmann, Booktitle = Proc. of ANNIE 2006, Pages = 623–632, Title = Supervised median clustering, ISBN = 0-7918-0256-6, Year = 2006</enrichment>
    <enrichment key="opus.import.dataHash">md5:10bd28de6cd2a49665f280377abf0665</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>B. Hammer</author>
    <author>A. Hasenfuss</author>
    <author>Frank-Michael Schleif</author>
    <author>T. Villmann</author>
  </doc>
  <doc>
    <id>6040</id>
    <completedYear/>
    <publishedYear>2006</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>541</pageFirst>
    <pageLast>548</pageLast>
    <pageNumber>8</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Machine Learning and Soft-Computing in Bioinformatics - A Short Journey</title>
    <parentTitle language="eng">Proc. of FLINS 2006</parentTitle>
    <identifier type="isbn">981-256-690-2</identifier>
    <enrichment key="opus.import.data">@INPROCEEDINGSSchleif2006k, Author = F.-M. Schleif and T. Elssner and M. Kostrzewa and T. Villmann and B. Hammer, Booktitle = Proc. of FLINS 2006, Pages = 541–548, Title = Machine Learning and Soft-Computing in Bioinformatics - A Short Journey, ISBN = 981-256-690-2, Publisher = World Scientific Press, Year = 2006</enrichment>
    <enrichment key="opus.import.dataHash">md5:485478703ddb4fd9cc2b798b1d66eca6</enrichment>
    <enrichment key="opus.import.date">2025-07-15T08:47:15+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpzbxNGL</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6876159341a060.14275529</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <author>Frank-Michael Schleif</author>
    <author>T. Elssner</author>
    <author>M. Kostrzewa</author>
    <author>T. Villmann</author>
    <author>B. Hammer</author>
  </doc>
</export-example>
