TY - JOUR A1 - Schorn, Michelle A. A1 - Verhoeven, Stefan A1 - Ridder, Lars A1 - Huber, Florian A1 - Acharya, Deepa D. A1 - Aksenov, Alexander A. A1 - Aleti, Gajender A1 - Moghaddam, Jamshid Amiri A1 - Aron, Allegra T. A1 - Aziz, Saefuddin A1 - Bauermeister, Anelize A1 - Bauman, Katherine D. A1 - Baunach, Martin A1 - Beemelmanns, Christine A1 - Beman, J. Michael A1 - Berlanga-Clavero, María Victoria A1 - Blacutt, Alex A. A1 - Bode, Helge B. A1 - Boullie, Anne A1 - Brejnrod, Asker A1 - Bugni, Tim S. A1 - Calteau, Alexandra A1 - Cao, Liu A1 - Carrión, Víctor J. A1 - Castelo-Branco, Raquel A1 - Chanana, Shaurya A1 - Chase, Alexander B. A1 - Chevrette, Marc G. A1 - Costa-Lotufo, Leticia V. A1 - Crawford, Jason M. A1 - Currie, Cameron R. A1 - Cuypers, Bart A1 - Dang, Tam A1 - de Rond, Tristan A1 - Demko, Alyssa M. A1 - Dittmann, Elke A1 - Du, Chao A1 - Drozd, Christopher A1 - Dujardin, Jean-Claude A1 - Dutton, Rachel J. A1 - Edlund, Anna A1 - Fewer, David P. A1 - Garg, Neha A1 - Gauglitz, Julia M. A1 - Gentry, Emily C. A1 - Gerwick, Lena A1 - Glukhov, Evgenia A1 - Gross, Harald A1 - Gugger, Muriel A1 - Guillén Matus, Dulce G. A1 - Helfrich, Eric J. N. A1 - Hempel, Benjamin-Florian A1 - Hur, Jae-Seoun A1 - Iorio, Marianna A1 - Jensen, Paul R. A1 - Kang, Kyo Bin A1 - Kaysser, Leonard A1 - Kelleher, Neil L. A1 - Kim, Chung Sub A1 - Kim, Ki Hyun A1 - Koester, Irina A1 - König, Gabriele M. A1 - Leao, Tiago A1 - Lee, Seoung Rak A1 - Lee, Yi-Yuan A1 - Li, Xuanji A1 - Little, Jessica C. A1 - Maloney, Katherine N. A1 - Männle, Daniel A1 - Martin H, Christian A1 - McAvoy, Andrew C. A1 - Metcalf, Willam W. A1 - Mohimani, Hosein A1 - Molina-Santiago, Carlos A1 - Moore, Bradley S. A1 - Mullowney, Michael W. A1 - Muskat, Mitchell A1 - Nothias, Louis-Félix A1 - O'Neill, Ellis C. A1 - Parkinson, Elizabeth I. A1 - Petras, Daniel A1 - Piel, Jörn A1 - Pierce, Emily C. A1 - Pires, Karine A1 - Reher, Raphael A1 - Romero, Diego A1 - Roper, M. Caroline A1 - Rust, Michael A1 - Saad, Hamada A1 - Saenz, Carmen A1 - Sanchez, Laura M. A1 - Sørensen, Søren Johannes A1 - Sosio, Margherita A1 - Süssmuth, Roderich D. A1 - Sweeney, Douglas A1 - Tahlan, Kapil A1 - Thomson, Regan J. A1 - Tobias, Nicholas J. A1 - Trindade-Silva, Amaro E. A1 - van Wezel, Gilles P. A1 - Wang, Mingxun A1 - Weldon, Kelly C. A1 - Zhang, Fan A1 - Ziemert, Nadine A1 - Duncan, Katherine R. A1 - Crüsemann, Max A1 - Rogers, Simon A1 - Dorrestein, Pieter C. A1 - Medema, Marnix H. A1 - van der Hooft, Justin J. J. T1 - A community resource for paired genomic and metabolomic data mining JF - Nature Chemical Biology Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34708 UR - http://www.ncbi.nlm.nih.gov/pubmed/33589842 SN - 1552-4469 N1 - Additional information: Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41589-020-00724-z. VL - 17 IS - 4 SP - 363 EP - 368 PB - Nature ER - TY - JOUR A1 - Migueles, Jairo H. A1 - Rowlands, Alex V. A1 - Huber, Florian A1 - Sabia, Séverine A1 - van Hees, Vincent T. T1 - GGIR: A Research Community–Driven Open Source R Package for Generating Physical Activity and Sleep Outcomes From Multi-Day Raw Accelerometer Data JF - Journal for the Measurement of Physical Behaviour Y1 - 2019 U6 - https://doi.org/10.1123/jmpb.2018-0063 SN - 2575-6605 VL - 2 IS - 3 SP - 188 EP - 196 PB - Human Kinetics ER - TY - JOUR A1 - Beniddir, Mehdi A. A1 - Kang, Kyo Bin A1 - Genta-Jouve, Grégory A1 - Huber, Florian A1 - Rogers, Simon A1 - van der Hooft, Justin J. J. T1 - Advances in decomposing complex metabolite mixtures using substructure- and network-based computational metabolomics approaches JF - Natural Product Reports Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34772 SN - 1460-4752 VL - 38 IS - 11 SP - 1967 EP - 1993 PB - The Royal Society of Chemistry ER - TY - JOUR A1 - Huber, Florian A1 - Boire, Adeline A1 - López, Magdalena Preciado A1 - Koenderink, Gijsje H. T1 - Cytoskeletal crosstalk: when three different personalities team up JF - Current Opinion in Cell Biology Y1 - 2015 U6 - https://doi.org/10.1016/j.ceb.2014.10.005 SN - 1879-0410 VL - 32 SP - 39 EP - 47 PB - Elsevier ER - TY - JOUR A1 - Huber, Florian A1 - Käs, Josef T1 - Self-regulative organization of the cytoskeleton JF - Cytoskeleton N2 - Despite its impressive complexity the cytoskeleton succeeds to persistently organize itself and thus the cells' interior. In contrast to classical man-made machines, much of the cellular organization originates from inherent self-assembly and self-organization allowing a high degree of autonomy for various functional units. Recent experimental and theoretical studies revealed numerous examples of cytoskeleton components that arrange and organize in a self-regulative way. In the present review we want to shortly summarize some of the principle mechanisms that are able to inherently trigger and regulate the cytoskeleton organization. Although taken individually most of these regulative principles are rather simple with intuitively predictable consequences, combinations of two or more of these mechanisms can quickly give rise to very complex, unexpected behavior and might even be able to explain the formation of different functional units out of a common pool of available building blocks. Y1 - 2011 UR - http://www.ncbi.nlm.nih.gov/pubmed/21438165 U6 - https://doi.org/10.1002/cm.20509 SN - 1949-3592 N1 - Acknowledgment We would like to thank Dan Strehle for critical reading ofthis manuscript. This work was funded by the Leipzig School of Natural Sciences ‘‘BuildMoNa’’ as well as bythe Sa¨chsische Aufbaubank project number 13403 VL - 68 IS - 5 SP - 259 EP - 265 PB - Wiley ER - TY - JOUR A1 - Huber, Florian A1 - Käs, Josef A1 - Stuhrmann, Björn T1 - Growing actin networks form lamellipodium and lamellum by self-assembly JF - Biophysical Journal N2 - Many different cell types are able to migrate by formation of a thin actin-based cytoskeletal extension. Recently, it became evident that this extension consists of two distinct substructures, designated lamellipodium and lamellum, which differ significantly in their kinetic and kinematic properties as well as their biochemical composition. We developed a stochastic two-dimensional computer simulation that includes chemical reaction kinetics, G-actin diffusion, and filament transport to investigate the formation of growing actin networks in migrating cells. Model parameters were chosen based on experimental data or theoretical considerations. In this work, we demonstrate the system's ability to form two distinct networks by self-organization. We found a characteristic transition in mean filament length as well as a distinct maximum in depolymerization flux, both within the first 1-2 microm. The separation into two distinct substructures was found to be extremely robust with respect to initial conditions and variation of model parameters. We quantitatively investigated the complex interplay between ADF/cofilin and tropomyosin and propose a plausible mechanism that leads to spatial separation of, respectively, ADF/cofilin- or tropomyosin-dominated compartments. Tropomyosin was found to play an important role in stabilizing the lamellar actin network. Furthermore, the influence of filament severing and annealing on the network properties is explored, and simulation data are compared to existing experimental data. KW - Open Archive Y1 - 2008 UR - http://www.ncbi.nlm.nih.gov/pubmed/18708450 U6 - https://doi.org/10.1529/biophysj.108.134817 SN - 1542-0086 VL - 95 IS - 12 SP - 5508 EP - 5523 PB - Biophysical Society ER - TY - JOUR A1 - Huber, Florian A1 - Schnauß, Jörg A1 - Rönicke, S. A1 - Rauch, P. A1 - Müller, K. A1 - Fütterer, C. A1 - Käs, Josef T1 - Emergent complexity of the cytoskeleton: from single filaments to tissue JF - Advances in Physics N2 - Despite their overwhelming complexity, living cells display a high degree of internal mechanical and functional organization which can largely be attributed to the intracellular biopolymer scaffold, the cytoskeleton. Being a very complex system far from thermodynamic equilibrium, the cytoskeleton's ability to organize is at the same time challenging and fascinating. The extensive amounts of frequently interacting cellular building blocks and their inherent multifunctionality permits highly adaptive behavior and obstructs a purely reductionist approach. Nevertheless (and despite the field's relative novelty), the physics approach has already proved to be extremely successful in revealing very fundamental concepts of cytoskeleton organization and behavior. This review aims at introducing the physics of the cytoskeleton ranging from single biopolymer filaments to multicellular organisms. Throughout this wide range of phenomena, the focus is set on the intertwined nature of the different physical scales (levels of complexity) that give rise to numerous emergent properties by means of self-organization or self-assembly. Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34812 UR - http://www.ncbi.nlm.nih.gov/pubmed/24748680 SN - 1460-6976 N1 - Acknowledgment: We thank Klaus Kroy, Dan Strehle, Tobias Kießling, Matti Gralka, Harald Herrmann, Denis Wirtz, and Michael Höckel for very helpful comments, discussions, and proof reading. We further like to thank Steve Pawlizak, Thomas Fuhs, Daniel Koch, BjöStuhrmann, and Franziska Wetzel for contributing data and additional illustrations. This work was supported by the graduate school “Building with Molecules and Nano-Objects” (BuildMoNa). VL - 62 IS - 1 SP - 1 EP - 112 PB - Taylor & Francis ER - TY - JOUR A1 - Huber, Florian A1 - Strehle, Dan A1 - Kaes, Josef T1 - Counterion-induced formation of regular actin bundle networks JF - Soft Matter Y1 - 2012 SN - 1744-6848 VL - 8 IS - 4 SP - 931 EP - 936 PB - Royal Society of Chemistry ER - TY - JOUR A1 - Huber, Florian A1 - Strehle, Dan A1 - Schnauß, Jörg A1 - Käs, Josef T1 - Formation of regularly spaced networks as a general feature of actin bundle condensation by entropic forces JF - New Journal of Physics KW - DOAJ Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34833 SN - 1367-2630 VL - 17 IS - 4 PB - IOP Publishing ER - TY - JOUR A1 - Huber, Florian A1 - van der Burg, Sven A1 - van der Hooft, Justin J. J. A1 - Ridder, Lars T1 - MS2DeepScore: a novel deep learning similarity measure to compare tandem mass spectra JF - Journal of Cheminformatics N2 - Mass spectrometry data is one of the key sources of information in many workflows in medicine and across the life sciences. Mass fragmentation spectra are generally considered to be characteristic signatures of the chemical compound they originate from, yet the chemical structure itself usually cannot be easily deduced from the spectrum. Often, spectral similarity measures are used as a proxy for structural similarity but this approach is strongly limited by a generally poor correlation between both metrics. Here, we propose MS2DeepScore: a novel Siamese neural network to predict the structural similarity between two chemical structures solely based on their MS/MS fragmentation spectra. Using a cleaned dataset of > 100,000 mass spectra of about 15,000 unique known compounds, we trained MS2DeepScore to predict structural similarity scores for spectrum pairs with high accuracy. In addition, sampling different model varieties through Monte-Carlo Dropout is used to further improve the predictions and assess the model's prediction uncertainty. On 3600 spectra of 500 unseen compounds, MS2DeepScore is able to identify highly-reliable structural matches and to predict Tanimoto scores for pairs of molecules based on their fragment spectra with a root mean squared error of about 0.15. Furthermore, the prediction uncertainty estimate can be used to select a subset of predictions with a root mean squared error of about 0.1. Furthermore, we demonstrate that MS2DeepScore outperforms classical spectral similarity measures in retrieving chemically related compound pairs from large mass spectral datasets, thereby illustrating its potential for spectral library matching. Finally, MS2DeepScore can also be used to create chemically meaningful mass spectral embeddings that could be used to cluster large numbers of spectra. Added to the recently introduced unsupervised Spec2Vec metric, we believe that machine learning-supported mass spectral similarity measures have great potential for a range of metabolomics data processing pipelines. KW - DOAJ Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34847 UR - http://www.ncbi.nlm.nih.gov/pubmed/34715914 SN - 1758-2946 N1 - J.J.J.v.d.H. acknowledges funding from an ASDI eScience grant, ASDI.2017.030, from the Netherlands eScience Center. VL - 13 IS - 1 PB - Cold Spring Harbor Laboratory ER - TY - JOUR A1 - Huber, Florian A1 - Verhoeven, Stefan A1 - Meijer, Christiaan A1 - Spreeuw, Hanno A1 - Castilla, Efraín A1 - Geng, Cunliang A1 - van der Hooft, Justin J. J. A1 - Rogers, Simon A1 - Belloum, Adam A1 - Diblen, Faruk A1 - Spaaks, Jurriaan H. T1 - matchms - processing and similarity evaluation of mass spectrometry data JF - Journal of Open Source Software KW - DOAJ Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34856 SN - 2475-9066 VL - 5 IS - 52 PB - Cold Spring Harbor Laboratory ER - TY - JOUR A1 - Preciado López, Magdalena A1 - Huber, Florian A1 - Grigoriev, Ilya A1 - Steinmetz, Michel O. A1 - Akhmanova, Anna A1 - Dogterom, Marileen A1 - Koenderink, Gijsje H. T1 - In vitro reconstitution of dynamic microtubules interacting with actin filament networks JF - Methods in Enzymology Y1 - 2014 U6 - https://doi.org/10.1016/B978-0-12-397924-7.00017-0 SN - 1557-7988 VL - 540 SP - 301 EP - 320 PB - Elsevier ER - TY - JOUR A1 - Preciado López, Magdalena A1 - Huber, Florian A1 - Grigoriev, Ilya A1 - Steinmetz, Michel O. A1 - Akhmanova, Anna A1 - Koenderink, Gijsje H. A1 - Dogterom, Marileen T1 - Actin-microtubule coordination at growing microtubule ends JF - Nature Communications N2 - To power dynamic processes in cells, the actin and microtubule cytoskeletons organize into complex structures. Although it is known that cytoskeletal coordination is vital for cell function, the mechanisms by which cross-linking proteins coordinate actin and microtubule activities remain poorly understood. In particular, it is unknown how the distinct mechanical properties of different actin architectures modulate the outcome of actin-microtubule interactions. To address this question, we engineered the protein TipAct, which links growing microtubule ends via end-binding proteins to actin filaments. We show that growing microtubules can be captured and guided by stiff actin bundles, leading to global actin-microtubule alignment. Conversely, growing microtubule ends can transport, stretch and bundle individual actin filaments, thereby globally defining actin filament organization. Our results provide a physical basis to understand actin-microtubule cross-talk, and reveal that a simple cross-linker can enable a mechanical feedback between actin and microtubule organization that is relevant to diverse biological contexts. KW - DOAJ Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34878 SN - 2041-1723 VL - 5 PB - Springer Nature ER - TY - JOUR A1 - Siccardi, Stefano A1 - Adamatzky, Andrew A1 - Tuszyński, Jack A1 - Huber, Florian A1 - Schnauß, Jörg T1 - Actin networks voltage circuits JF - Physical Review E Y1 - 2020 U6 - https://doi.org/10.1103/PhysRevE.101.052314 SN - 2470-0053 VL - 101 IS - 5-1 PB - American Physical Society (APS) ER - TY - JOUR A1 - Smith, David A1 - Gentry, Brian A1 - Stuhrmann, Björn A1 - Huber, Florian A1 - Strehle, D. A.N. A1 - Brunner, Claudia A1 - Koch, Daniel A1 - Steinbeck, Matthias A1 - Betz, Timo A1 - Käs, Josef A. T1 - The cytoskeleton: An active polymer-based scaffold JF - Biophysical Reviews and Letters Y1 - 2009 U6 - https://doi.org/10.1142/S1793048009000983 SN - 1793-7035 VL - 04 SP - 179 EP - 208 ER - TY - JOUR A1 - Stuhrmann, Björn A1 - Huber, Florian A1 - Käs, Josef T1 - Robust organizational principles of protrusive biopolymer networks in migrating living cells JF - Plos One N2 - Cell migration is associated with the dynamic protrusion of a thin actin-based cytoskeletal extension at the cell front, which has been shown to consist of two different substructures, the leading lamellipodium and the subsequent lamellum. While the formation of the lamellipodium is increasingly well understood, organizational principles underlying the emergence of the lamellum are just beginning to be unraveled. We report here on a 1D mathematical model which describes the reaction-diffusion processes of a polarized actin network in steady state, and reproduces essential characteristics of the lamellipodium-lamellum system. We observe a steep gradient in filament lengths at the protruding edge, a local depolymerization maximum a few microns behind the edge, as well as a differential dominance of the network destabilizer ADF/cofilin and the stabilizer tropomyosin. We identify simple and robust organizational principles giving rise to the derived network characteristics, uncoupled from the specifics of any molecular implementation, and thus plausibly valid across cell types. An analysis of network length dependence on physico-chemical system parameters implies that to limit array treadmilling to cellular dimensions, network growth has to be truncated by mechanisms other than aging-induced depolymerization, e.g., by myosin-associated network dissociation at the transition to the cell body. Our work contributes to the analytical understanding of the cytoskeletal extension's bisection into lamellipodium and lamellum and sheds light on how cells organize their molecular machinery to achieve motility. KW - DOAJ Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34901 SN - 1932-6203 N1 - Funding: This work has been supported by the Leipzig Graduate College ‘‘GK 1097 InterNeuro - Interdisciplinary Approaches in Cellular Neuroscience’’ (http:// www.uni-leipzig.de/˜ineuro/) and the Graduate School ‘‘Leipzig School of Natural Sciences - Building with Molecules and Nano-objects (BuildMoNa)’’ (http://www. buildmona.de/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. VL - 6 IS - 1 PB - Public Library of Science (PLoS) ER - TY - JOUR A1 - Adamatzky, Andrew A1 - Huber, Florian A1 - Schnauß, Jörg T1 - Computing on actin bundles network JF - Scientific Reports N2 - Actin filaments are conductive to ionic currents, mechanical and voltage solitons. These travelling localisations can be utilised to generate computing circuits from actin networks. The propagation of localisations on a single actin filament is experimentally unfeasible to control. Therefore, we consider excitation waves propagating on bundles of actin filaments. In computational experiments with a two-dimensional slice of an actin bundle network we show that by using an arbitrary arrangement of electrodes, it is possible to implement two-inputs-one-output circuits. Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34665 UR - http://www.ncbi.nlm.nih.gov/pubmed/31685834 SN - 2045-2322 VL - 9 IS - 1 PB - Springer Nature ER - TY - JOUR A1 - Adamatzky, Andrew A1 - Schnauß, Jörg A1 - Huber, Florian T1 - Actin droplet machine JF - Royal Society Open Science N2 - The actin droplet machine is a computer model of a three-dimensional network of actin bundles developed in a droplet of a physiological solution, which implements mappings of sets of binary strings. The actin bundle network is conductive to travelling excitations, i.e. impulses. The machine is interfaced with an arbitrary selected set of k electrodes through which stimuli, binary strings of length k represented by impulses generated on the electrodes, are applied and responses are recorded. The responses are recorded in a form of impulses and then converted to binary strings. The machine's state is a binary string of length k: if there is an impulse recorded on the ith electrode, there is a '1' in the ith position of the string, and '0' otherwise. We present a design of the machine and analyse its state transition graphs. We envisage that actin droplet machines could form an elementary processor of future massive parallel computers made from biopolymers. Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34675 UR - http://www.ncbi.nlm.nih.gov/pubmed/31903204 SN - 2054-5703 N1 - A.A. was partially supported by EPSRC grant no. EP/P016677/1. The authors declare that they have no competing interests. VL - 6 IS - 12 PB - Royal Soc. Publ. ER - TY - JOUR A1 - Huber, Florian A1 - Ridder, Lars A1 - Verhoeven, Stefan A1 - Spaaks, Jurriaan H. A1 - Diblen, Faruk A1 - Rogers, Simon A1 - van der Hooft, Justin J. J. T1 - Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships JF - PLOS Computational Biology N2 - Spectral similarity is used as a proxy for structural similarity in many tandem mass spectrometry (MS/MS) based metabolomics analyses such as library matching and molecular networking. Although weaknesses in the relationship between spectral similarity scores and the true structural similarities have been described, little development of alternative scores has been undertaken. Here, we introduce Spec2Vec, a novel spectral similarity score inspired by a natural language processing algorithm-Word2Vec. Spec2Vec learns fragmental relationships within a large set of spectral data to derive abstract spectral embeddings that can be used to assess spectral similarities. Using data derived from GNPS MS/MS libraries including spectra for nearly 13,000 unique molecules, we show how Spec2Vec scores correlate better with structural similarity than cosine-based scores. We demonstrate the advantages of Spec2Vec in library matching and molecular networking. Spec2Vec is computationally more scalable allowing structural analogue searches in large databases within seconds. Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34687 UR - http://www.ncbi.nlm.nih.gov/pubmed/33591968 SN - 1553-7358 N1 - Data Availability Statement: The pre-processed, cleaned dataset with all positive ionization mode spectra can be downloaded from https://doi.org/10.5281/zenodo.3978118, the original raw data can be accessed from https://doi.org/10.5281/zenodo.3979010. Funding: J.J.J.v.d.H. acknowledges funding from an ASDI eScience grant, ASDI.2017.030, from the Netherlands eScience Center—NLeSC, www.esciencecenter.nl, The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. VL - 17 IS - 2 PB - Cold Spring Harbor Laboratory ER - TY - JOUR A1 - Mullowney, Michael W. A1 - Duncan, Katherine R. A1 - Elsayed, Somayah S. A1 - Garg, Neha A1 - van der Hooft, Justin J. J. A1 - Martin, Nathaniel I. A1 - Meijer, David A1 - Terlouw, Barbara R. A1 - Biermann, Friederike A1 - Blin, Kai A1 - Durairaj, Janani A1 - Gorostiola González, Marina A1 - Helfrich, Eric J. N. A1 - Huber, Florian A1 - Leopold-Messer, Stefan A1 - Rajan, Kohulan A1 - de Rond, Tristan A1 - van Santen, Jeffrey A. A1 - Sorokina, Maria A1 - Balunas, Marcy J. A1 - Beniddir, Mehdi A. A1 - van Bergeijk, Doris A. A1 - Carroll, Laura M. A1 - Clark, Chase M. A1 - Clevert, Djork-Arné A1 - Dejong, Chris A. A1 - Du, Chao A1 - Ferrinho, Scarlet A1 - Grisoni, Francesca A1 - Hofstetter, Albert A1 - Jespers, Willem A1 - Kalinina, Olga V. A1 - Kautsar, Satria A. A1 - Kim, Hyunwoo A1 - Leao, Tiago F. A1 - Masschelein, Joleen A1 - Rees, Evan R. A1 - Reher, Raphael A1 - Reker, Daniel A1 - Schwaller, Philippe A1 - Segler, Marwin A1 - Skinnider, Michael A. A1 - Walker, Allison S. A1 - Willighagen, Egon L. A1 - Zdrazil, Barbara A1 - Ziemert, Nadine A1 - Goss, Rebecca J. M. A1 - Guyomard, Pierre A1 - Volkamer, Andrea A1 - Gerwick, William H. A1 - Kim, Hyun Uk A1 - Müller, Rolf A1 - van Wezel, Gilles P. A1 - van Westen, Gerard J. P. A1 - Hirsch, Anna K. H. A1 - Linington, Roger G. A1 - Robinson, Serina L. A1 - Medema, Marnix H. T1 - Artificial intelligence for natural product drug discovery JF - Nature Reviews Drug Discovery KW - Maschinelles Lernen KW - Arzneimittelforschung KW - Deep learning KW - Omics-Technologie Y1 - 2023 U6 - https://doi.org/10.1038/s41573-023-00774-7 SN - 1474-1776 VL - 22 IS - 11 SP - 895 EP - 916 PB - Springer Nature ER - TY - CHAP A1 - Gaudry, Arnaud A1 - Huber, Florian A1 - Flückiger, Julien A1 - Quirós, L A1 - Rutz, Adriano A1 - Kaiser, M A1 - Grondin, A A1 - Marcourt, Laurence A1 - Ferreira Queiroz, E A1 - Wolfender, Jean-Luc A1 - Allard, Pierre-Marie T1 - Short Lecture “Mass spectrometry-based sample vectorization for exploration of large chemodiverse datasets and efficient identification of new antiparasitic compounds” T2 - Planta Medica KW - Massenspektrometrie KW - Naturstoffchemie KW - Antiparasitäres Mittel KW - Arzneimittelforschung Y1 - 2022 U6 - https://doi.org/10.1055/s-0042-1758983 SN - 1439-0221 VL - 88 IS - 15 PB - Thieme ER - TY - CHAP A1 - Adamatzky, Andrew A1 - Huber, Florian A1 - Schnauß, Jörg ED - Adamatzky, Andrew T1 - Computing on Actin Bundles Network T2 - Actin Computation: Unlocking the Potential of Actin Filaments for Revolutionary Computing System KW - Actin-Filament KW - Informationsverarbeitung KW - Bioinformatik Y1 - 2024 SN - 9789811285066 U6 - https://doi.org/10.1142/9789811285073_0013 SN - 2737-520X VL - Wspc Book Series in Unconventional Computing, Vol. 3 SP - 245 EP - 261 PB - WORLD SCIENTIFIC ER - TY - CHAP A1 - Siccardi, Stefano A1 - Adamatzky, Andrew A1 - Tuszyński, Jack A1 - Huber, Florian A1 - Schnauß, Jörg ED - Adamatzky, Andrew T1 - Actin Networks Voltage Circuits T2 - Actin Computation: Unlocking the Potential of Actin Filaments for Revolutionary Computing Systems KW - Actin-Filament KW - Informationsverarbeitung KW - Bioinformatik Y1 - 2024 SN - 9789811285066 U6 - https://doi.org/10.1142/9789811285073_0006 SN - 2737-520X VL - Wspc Book Series in Unconventional Computing, Vol. 3 SP - 123 EP - 143 PB - WORLD SCIENTIFIC ER -