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1Lifeworld-References and Future Prospect
S. Hummel, M. Brodacz-Geier, and S. Dahanayake. page 162--171. University of Graz, (2021)
3 months ago by @scadsfct
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1Stolperstein oder Kompetenzstufe: Die Studieneingangsphase und ihre Bedeutung für die Wissenschaftssozialisation von Studierenden
R. Egger, and S. Hummel. Lernweltforschung SPRINGER VS/SPRINGER FACHMEDIEN, Deutschland, (2020)
3 months ago by @scadsfct
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2Intermediate Fusion for Multimodal Product Matching
J. Pollack, H. Köpcke, and E. Rahm. (2024)
3 months ago by @scadsfct
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2Towards self-configuring knowledge graph construction pipelines using llms-a case study with rml
M. Hofer, J. Frey, and E. Rahm. Fifth International Workshop on Knowledge Graph Construction@ ESWC2024, (2024)
3 months ago by @scadsfct
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2Generating Synthetic Health Sensor Data for Privacy-Preserving Wearable Stress Detection
L. Lange, N. Wenzlitschke, and E. Rahm. Sensors, 24 (10): 3052 (2024)
3 months ago by @scadsfct
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2Graph-based Active Learning for Entity Cluster Repair
V. Christen, D. Obraczka, M. Hofer, M. Franke, and E. Rahm. arXiv preprint arXiv:2401.14992, (2024)
3 months ago by @scadsfct
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2Physics-informed deep learning to quantify anomalies for real-time fault mitigation in 3D printing
B. Uhrich, N. Pfeifer, M. Schäfer, O. Theile, and E. Rahm. Applied Intelligence, 54 (6): 4736--4755 (2024)
3 months ago by @scadsfct
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2Neural Diffusion Graph Convolutional Network for Predicting Heat Transfer in Selective Laser Melting
B. Uhrich, T. Häntschel, M. Schäfer, and E. Rahm. International Workshop on Combinatorial Image Analysis, page 150--164. Springer, (2024)
3 months ago by @scadsfct
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2BiMAE - A Bimodal Masked Autoencoder Architecture for Single-Label Hyperspectral Image Classification
M. Kukushkin, M. Bogdan, and T. Schmid. IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024 - Workshops, Seattle, WA, USA, June 17-18, 2024, page 2987--2996. IEEE, (2024)
3 months ago by @scadsfct
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2Genomic events stratifying prognosis of early gastric cancer
C. Molinari, L. Solaini, F. Rebuzzi, G. Tedaldi, D. Angeli, E. Petracci, D. Prascevic, J. Ewald, E. Rahm, M. Canale and 1 other author(s). Gastric Cancer, (2024)
3 months ago by @scadsfct
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1Strategies of rational and structure-driven vaccine design for Arenaviruses
A. Peter, D. Hoffmann, J. Klier, C. Lange, J. Möller, V. Most, C. Wüst, M. Beining, S. Gülesen, H. Junker and 3 other author(s). Infection, Genetics and Evolution, (2024)
3 months ago by @scadsfct
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1Learning to reconstruct the bubble distribution with conductivity maps using Invertible Neural Networks and Error Diffusion
N. Kumar, L. Krause, T. Wondrak, S. Eckert, K. Eckert, and S. Gumhold. arXiv preprint arXiv:2307.02496, (2023)
3 months ago by @scadsfct
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1Computational Performance Aware Benchmarking of Unsupervised Concept Drift Detection.
E. Werner, N. Kumar, S. Torge, M. Lieber, A. Raj, S. Gumhold, and W. Nagel. CoRR, (2023)
3 months ago by @scadsfct
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1FusionINN: Invertible Image Fusion for Brain Tumor Monitoring
N. Kumar, Z. Tao, J. Singh, Y. Li, P. Sun, B. Zhao, and S. Gumhold. arXiv preprint arXiv:2403.15769, (2024)
3 months ago by @scadsfct
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1A taxonomy of uncertainty events in visual analytics
C. Gillmann, R. Maack, F. Raith, J. Pérez, and G. Scheuermann. IEEE Computer Graphics and Applications, (2023)
3 months ago by @scadsfct
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1Visualizing Similarity of Pathline Dynamics in 2D Flow Fields
B. Nsonga, and G. Scheuermann. 2023 IEEE Visualization and Visual Analytics (VIS), page 71--75. IEEE, (2023)
3 months ago by @scadsfct
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1Visualizing statistical complexity in 3d turbulent flows using a robust entropy calculation method
A. Präger, B. Nsonga, and G. Scheuermann. (2022)
3 months ago by @scadsfct
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1Adeno-associated virus serotype 2 capsid variants for improved liver-directed gene therapy
N. Meumann, M. Cabanes-Creus, M. Ertelt, R. Navarro, J. Lucifora, Q. Yuan, K. Nien-Huber, A. Abdelrahman, X. Vu, L. Zhang and 1 other author(s). Hepatology, 77 (3): 802--815 (2023)
3 months ago by @scadsfct
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1Hardware-Agnostic Interactive Exascale In Situ Visualization of Particle-In-Cell Simulations
F. Meyer, B. Hernandez, R. Pausch, R. Widera, D. Groß, S. Bastrakov, A. Huebl, G. Juckeland, J. Kelling, M. Leinhauser and 1 other author(s). Proceedings of the Platform for Advanced Scientific Computing Conference, page 1--14. (2023)
3 months ago by @scadsfct
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1Divergent Pairwise Epistasis in the Context of Unstable Membrane Protein Variants
L. Chamness, C. Kuntz, A. McKee, W. Penn, C. Hemmerich, D. Rusch, H. Woods, Dyotima, J. Meiler, and J. Schlebach. (December 2023)
3 months ago by @scadsfct
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1Self-supervised machine learning methods for protein design improve sampling, but not the identification of high-fitness variants
M. Ertelt, R. Moretti, J. Meiler, and C. Schoeder. (June 2024)
3 months ago by @scadsfct
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1Interpretable deep-learning pKa prediction for small molecule drugs via atomic sensitivity analysis
J. DeCorte, B. Brown, and J. Meiler. (June 2024)
3 months ago by @scadsfct
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1Biasing AlphaFold2 to predict GPCRs and kinases with user-defined functional or structural properties
D. Sala, P. Hildebrand, and J. Meiler. Frontiers in Molecular Biosciences, (February 2023)
3 months ago by @scadsfct
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1VUStruct: a compute pipeline for high throughput and personalized structural biology
C. Moth, J. Sheehan, A. Mamun, R. Sivley, A. Gulsevin, D. Rinker, J. Capra, and J. Meiler. (August 2024)
3 months ago by @scadsfct
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1Computer-Aided Design and Biological Evaluation of Diazaspirocyclic D4R Antagonists
C. Jones, B. Brown, D. Schultz, J. Engers, V. Kramlinger, J. Meiler, and C. Lindsley. ACS Chemical Neuroscience, 15 (12): 2396â2407 (June 2024)
3 months ago by @scadsfct
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1Approximating conformational Boltzmann distributions with AlphaFold2 predictions
B. Brown, R. Stein, J. Meiler, and H. Mchaourab. (August 2023)
3 months ago by @scadsfct
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1Template-free prediction of a new monotopic membrane protein fold and assembly by AlphaFold2
A. Gulsevin, B. Han, J. Porta, H. Mchaourab, J. Meiler, and A. Kenworthy. Biophysical Journal, 122 (11): 2041â2052 (June 2023)
3 months ago by @scadsfct
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1Template-free prediction of a new monotopic membrane protein fold and oligomeric assembly by Alphafold2
A. Gulsevin, B. Han, J. Porta, H. Mchaourab, J. Meiler, and A. Kenworthy. (July 2022)
3 months ago by @scadsfct
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1Benchmarking Peptide Structure Prediction with AlphaFold2
A. Gulsevin, and J. Meiler. (February 2022)
3 months ago by @scadsfct
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1Modeling conformational states of proteins with AlphaFold
D. Sala, F. Engelberger, H. Mchaourab, and J. Meiler. Current Opinion in Structural Biology, (August 2023)
3 months ago by @scadsfct
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1Heterogeneity of the GFP fitness landscape and data-driven protein design
L. Gonzalez Somermeyer, A. Fleiss, A. Mishin, N. Bozhanova, A. Igolkina, J. Meiler, M. Alaball Pujol, E. Putintseva, K. Sarkisyan, and F. Kondrashov. eLife, (May 2022)
3 months ago by @scadsfct
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1An Active Learning Framework Improves Tumor Variant Interpretation
A. Blee, B. Li, T. Pecen, J. Meiler, Z. Nagel, J. Capra, and W. Chazin. Cancer Research, 82 (15): 2704â2715 (June 2022)
3 months ago by @scadsfct
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1Sampling alternative conformational states of transporters and receptors with AlphaFold2
D. del Alamo, D. Sala, H. Mchaourab, and J. Meiler. eLife, (March 2022)
3 months ago by @scadsfct
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1Interpretable Chirality-Aware Graph Neural Network for Quantitative Structure Activity Relationship Modeling in Drug Discovery
Y. Liu, Y. Wang, O. Vu, R. Moretti, B. Bodenheimer, J. Meiler, and T. Derr. Proceedings of the AAAI Conference on Artificial Intelligence, 37 (12): 14356â14364 (June 2023)
3 months ago by @scadsfct
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1Benchmarking AlphaMissense Pathogenicity Predictions Against Cystic Fibrosis Variants
E. McDonald, K. Oliver, J. Schlebach, J. Meiler, and L. Plate. (October 2023)
3 months ago by @scadsfct
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1SuperWater: Predicting Water Molecule Positions on Protein Structures by Generative AI
X. Kuang, z. su, Y. Liu, X. Lin, J. Smith, T. Derr, Y. Wu, and J. Meiler. (November 2024)
3 months ago by @scadsfct
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1Approximating Projections of Conformational Boltzmann Distributions with AlphaFold2 Predictions: Opportunities and Limitations
B. Brown, R. Stein, J. Meiler, and H. Mchaourab. Journal of Chemical Theory and Computation, 20 (3): 1434â1447 (January 2024)
3 months ago by @scadsfct
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1Benchmarking AlphaMissense pathogenicity predictions against cystic fibrosis variants
E. McDonald, K. Oliver, J. Schlebach, J. Meiler, and L. Plate. PLOS ONE, 19 (1): e0297560 (January 2024)
3 months ago by @scadsfct
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1Machine learning application to predict binding affinity between peptide containing non-canonical amino acids and HLA0201
S. Jiang, Z. Su, N. Bloodworth, Y. Liu, C. Martina, D. Harrison, and J. Meiler. (November 2024)
3 months ago by @scadsfct
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1Introduction to the BioChemical Library (BCL): An Application-Based Open-Source Toolkit for Integrated Cheminformatics and Machine Learning in Computer-Aided Drug Discovery
B. Brown, O. Vu, A. Geanes, S. Kothiwale, M. Butkiewicz, E. Lowe, R. Mueller, R. Pape, J. Mendenhall, and J. Meiler. Frontiers in Pharmacology, (February 2022)
3 months ago by @scadsfct
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1Computational epitope mapping of class I fusion proteins using low complexity supervised learning methods
M. Fischer, J. Crowe, and J. Meiler. PLOS Computational Biology, 18 (12): e1010230 (December 2022)
3 months ago by @scadsfct
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1Combining machine learning with structure-based protein design to predict and engineer post-translational modifications of proteins
M. Ertelt, V. Mulligan, J. Maguire, S. Lyskov, R. Moretti, T. Schiffner, J. Meiler, and C. Schoeder. PLOS Computational Biology, 20 (3): e1011939 (March 2024)
3 months ago by @scadsfct
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1Predicting the functional impact of KCNQ1 variants with artificial neural networks
S. Phul, G. Kuenze, C. Vanoye, C. Sanders, A. George, and J. Meiler. PLOS Computational Biology, 18 (4): e1010038 (April 2022)
3 months ago by @scadsfct
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1A Multitask Deep-Learning Method for Predicting Membrane Associations and Secondary Structures of Proteins
B. Li, J. Mendenhall, J. Capra, and J. Meiler. Journal of Proteome Research, 20 (8): 4089â4100 (July 2021)
3 months ago by @scadsfct
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1Autocorrelation descriptor improvements for QSAR: 2DA_Sign and 3DA_Sign
G. Sliwoski, J. Mendenhall, and J. Meiler. Journal of Computer-Aided Molecular Design, 30 (3): 209â217 (December 2015)
3 months ago by @scadsfct
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1Strandâloopâstrand motifs: Prediction of hairpins and diverging turns in proteins
M. Kuhn, J. Meiler, and D. Baker. Proteins: Structure, Function, and Bioinformatics, 54 (2): 282â288 (December 2003)
3 months ago by @scadsfct
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1Towards Generalizable Predictions for the Effects of Mutations on G-Protein Coupled Receptor Expression
C. Kuntz, H. Woods, A. McKee, N. Zelt, J. Mendenhall, J. Meiler, and J. Schlebach. (December 2021)
3 months ago by @scadsfct
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1Using Neural Networks for 13C NMR Chemical Shift PredictionâComparison with Traditional Methods
J. Meiler, W. Maier, M. Will, and R. Meusinger. Journal of Magnetic Resonance, 157 (2): 242â252 (August 2002)
3 months ago by @scadsfct
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13D Deep Learning for Biological Function Prediction from Physical Fields
V. Golkov, M. Skwark, A. Mirchev, G. Dikov, A. Geanes, J. Mendenhall, J. Meiler, and D. Cremers. 2020 International Conference on 3D Vision (3DV), (November 2020)
3 months ago by @scadsfct
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1Computational Methods in Drug Discovery
G. Sliwoski, S. Kothiwale, J. Meiler, and E. Lowe. Pharmacological Reviews, 66 (1): 334â395 (December 2013)
3 months ago by @scadsfct
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1BCL::EMAS â Enantioselective Molecular Asymmetry Descriptor for 3D-QSAR
G. Sliwoski, E. Lowe, M. Butkiewicz, and J. Meiler. Molecules, 17 (8): 9971â9989 (August 2012)
3 months ago by @scadsfct
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1A Novel Method for Guiding Protein-Ligand Docking with QSAR-Derived Pharmacophore Maps
S. DeLuca, and J. Meiler. Biophysical Journal, 100 (3): 394aâ395a (February 2011)
3 months ago by @scadsfct
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1Predicting the Functional Impact of KCNQ1 Variants with Artificial Neural Networks
S. Phul, G. Kuenze, C. Vanoye, C. Sanders, A. George, and J. Meiler. (December 2021)
3 months ago by @scadsfct
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1Deep Learning for Virtual Screening: Five Reasons to Use ROC Cost Functions
V. Golkov, A. Becker, D. Plop, D. Čuturilo, N. Davoudi, J. Mendenhall, R. Moretti, J. Meiler, and D. Cremers. (2020)
3 months ago by @scadsfct
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1Quantitative StructureâActivity Relationship Modeling of Kinase Selectivity Profiles
S. Kothiwale, C. Borza, A. Pozzi, and J. Meiler. Molecules, 22 (9): 1576 (September 2017)
3 months ago by @scadsfct
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1Automated Structure Elucidation of Organic Molecules from 13C NMR Spectra Using Genetic Algorithms and Neural Networks
J. Meiler, and M. Will. Journal of Chemical Information and Computer Sciences, 41 (6): 1535â1546 (October 2001)
3 months ago by @scadsfct
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1Heterogeneity of the GFP fitness landscape and data-driven protein design
L. Somermeyer, A. Fleiss, A. Mishin, N. Bozhanova, A. Igolkina, J. Meiler, M. Pujol, E. Putintseva, K. Sarkisyan, and F. Kondrashov. (December 2021)
3 months ago by @scadsfct
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1Coupled prediction of protein secondary and tertiary structure
J. Meiler, and D. Baker. Proceedings of the National Academy of Sciences, 100 (21): 12105â12110 (October 2003)
3 months ago by @scadsfct
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1Ligand-based virtual screen for the discovery of novel M5 inhibitor chemotypes
A. Geanes, H. Cho, K. Nance, K. McGowan, P. Conn, C. Jones, J. Meiler, and C. Lindsley. Bioorganic & Medicinal Chemistry Letters, 26 (18): 4487â4491 (September 2016)
3 months ago by @scadsfct
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1Sampling the conformational landscapes of transporters and receptors with AlphaFold2
D. del Alamo, D. Sala, H. Mchaourab, and J. Meiler. (November 2021)
3 months ago by @scadsfct
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1A unified hydrophobicity scale for multispan membrane proteins
J. Koehler, N. Woetzel, R. Staritzbichler, C. Sanders, and J. Meiler. Proteins: Structure, Function, and Bioinformatics, 76 (1): 13â29 (December 2008)
3 months ago by @scadsfct
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1BCL::Mol2Dâa robust atom environment descriptor for QSAR modeling and lead optimization
O. Vu, J. Mendenhall, D. Altarawy, and J. Meiler. Journal of Computer-Aided Molecular Design, 33 (5): 477â486 (April 2019)
3 months ago by @scadsfct
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1Neural Network Prediction of 13C NMR Chemical Shifts of Substituted Benzenes
J. Meiler, R. Meusinger, and M. Will. Monatshefte fÃ¼r Chemie / Chemical Monthly, 130 (9): 1089â1095 (September 1999)
3 months ago by @scadsfct
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1Improving quantitative structureâactivity relationship models using Artificial Neural Networks trained with dropout
J. Mendenhall, and J. Meiler. Journal of Computer-Aided Molecular Design, 30 (2): 177â189 (February 2016)
3 months ago by @scadsfct
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13D-QSAR CoMFA study of benzoxazepine derivatives as mGluR5 positive allosteric modulators
E. Lowe, A. Ferrebee, A. Rodriguez, P. Conn, and J. Meiler. Bioorganic & Medicinal Chemistry Letters, 20 (19): 5922â5924 (October 2010)
3 months ago by @scadsfct
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1General Purpose Structure-Based Drug Discovery Neural Network Score Functions with Human-Interpretable Pharmacophore Maps
B. Brown, J. Mendenhall, A. Geanes, and J. Meiler. Journal of Chemical Information and Modeling, 61 (2): 603â620 (January 2021)
3 months ago by @scadsfct
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1Application of machine learning approaches on quantitative structure activity relationships
M. Butkiewicz, R. Mueller, D. Selic, E. Dawson, and J. Meiler. 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, (March 2009)
3 months ago by @scadsfct
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1GPU-accelerated machine learning techniques enable QSAR modeling of large HTS data
E. Lowe, M. Butkiewicz, N. Woetzel, and J. Meiler. 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), (May 2012)
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1Bcl&#x2237;ChemInfo - Qualitative analysis of machine learning models for activation of HSD involved in Alzheimerâs Disease
M. Butkiewicz, E. Lowe, and J. Meiler. 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), (May 2012)
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1Fast Determination of 13C NMR Chemical Shifts Using Artificial Neural Networks
J. Meiler, R. Meusinger, and M. Will. Journal of Chemical Information and Computer Sciences, 40 (5): 1169â1176 (August 2000)
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1Epothilones: Quantitative Structure Activity Relations Studied by Support Vector Machines and Artificial Neural Networks
A. Bleckmann, and J. Meiler. QSAR & Combinatorial Science, 22 (7): 722â728 (October 2003)
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1Benchmarking Ligand-Based Virtual High-Throughput Screening with the PubChem Database
M. Butkiewicz, E. Lowe, R. Mueller, J. Mendenhall, P. Teixeira, C. Weaver, and J. Meiler. Molecules, 18 (1): 735â756 (January 2013)
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1Novel methods of automated structure elucidation based on 13C NMR spectroscopy
J. Meiler, and M. KÃ¶ck. Magnetic Resonance in Chemistry, 42 (12): 1042â1045 (October 2004)
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1Improved prediction of trans-membrane spans in proteins using an artificial neural network
J. Koehler, R. Mueller, and J. Meiler. 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, (March 2009)
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1Comparative analysis of machine learning techniques for the prediction of logP
E. Lowe, M. Butkiewicz, M. Spellings, A. Omlor, and J. Meiler. 2011 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), (April 2011)
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1Discovery of 2â(2âBenzoxazoyl amino)â4âArylâ5âCyanopyrimidine as Negative Allosteric Modulators (NAMs) of Metabotropic Glutamate Receptorâ5 (mGlu5): From an Artificial Neural Network Virtual Screen to an In Vivo Tool Compound
R. Mueller, E. Dawson, J. Meiler, A. Rodriguez, B. Chauder, B. Bates, A. Felts, J. Lamb, U. Menon, S. Jadhav and 9 other author(s). ChemMedChem, 7 (3): 406â414 (January 2012)
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1Citance-Contextualized Summarization of Scientific Papers
S. Syed, A. Hakimi, K. Al-Khatib, and M. Potthast. Findings of the Association for Computational Linguistics: EMNLP 2023, page 8551--8568. Singapore, Association for Computational Linguistics, (December 2023)
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1NetRank Recovers Known Cancer Hallmark Genes as Universal Biomarker Signature for Cancer Outcome Prediction
A. Al-Fatlawi, N. Afrin, C. Ozen, N. Malekian, and M. Schroeder. Frontiers in Bioinformatics, (March 2022)
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1Promiscuity in drug discovery on the verge of the structural revolution: recent advances and future chances
S. Bolz, and M. Schroeder. Expert Opinion on Drug Discovery, 18 (9): 973–985 (July 2023)
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1A genome-wide scan of wastewater E. coli for genes under positive selection: focusing on mechanisms of antibiotic resistance
N. Malekian, A. Agrawal, T. Berendonk, A. Al-Fatlawi, and M. Schroeder. Scientific Reports, (May 2022)
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1A community effort in SARS‐CoV‐2 drug discovery
J. Schimunek, P. Seidl, K. Elez, T. Hempel, T. Le, F. Noé, S. Olsson, L. Raich, R. Winter, H. Gokcan and 142 other author(s). Molecular Informatics, (November 2023)
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1An interaction-based drug discovery screen explains known SARS-CoV-2 inhibitors and predicts new compound scaffolds
P. Schake, K. Dishnica, F. Kaiser, C. Leberecht, V. Haupt, and M. Schroeder. Scientific Reports, (June 2023)
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1Decomposing compounds enables reconstruction of interaction fingerprints for structure-based drug screening
M. Adasme, S. Bolz, A. Al-Fatlawi, and M. Schroeder. Journal of Cheminformatics, (March 2022)
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1Targeting ion channels with ultra-large library screening for hit discovery
K. Melancon, P. Pliushcheuskaya, J. Meiler, and G. Künze. Frontiers in Molecular Neuroscience, (January 2024)
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1Ferric reduction by a CYBDOM protein counteracts increased iron availability in root meristems induced by phosphorus deficiency
R. Maniero, C. Picco, A. Hartmann, F. Engelberger, A. Gradogna, J. Scholz-Starke, M. Melzer, G. Künze, A. Carpaneto, N. von Wirén and 1 other author(s). Nature Communications, (January 2024)
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1Similar Binding Modes of cGMP Analogues Limit Selectivity in Modulating Retinal CNG Channels via the Cyclic Nucleotide-Binding Domain
P. Pliushcheuskaya, S. Kesh, E. Kaufmann, S. Wucherpfennig, F. Schwede, G. Künze, and V. Nache. ACS Chemical Neuroscience, 15 (8): 1652–1668 (April 2024)
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1Structural Studies on the Binding Mode of Bisphenols to PPARγ
A. Useini, I. Schwerin, G. Künze, and N. Sträter. Biomolecules, 14 (6): 640 (May 2024)
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1The First International Workshop on Open Web Search (WOWS)
S. Farzana, M. Fröbe, M. Granitzer, G. Hendriksen, D. Hiemstra, M. Potthast, and S. Zerhoudi. European Conference on Information Retrieval, page 426--431. Springer, (2024)
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1Impact and development of an Open Web Index for open web search
M. Granitzer, S. Voigt, N. Fathima, M. Golasowski, C. Guetl, T. Hecking, G. Hendriksen, D. Hiemstra, J. Martinovic, J. Mitrović and 1 other author(s). Journal of the Association for Information Science and Technology, 75 (5): 512--520 (2024)
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1Systematic Evaluation of Neural Retrieval Models on the Touché 2020 Argument Retrieval Subset of BEIR
N. Thakur, L. Bonifacio, M. Fröbe, A. Bondarenko, E. Kamalloo, M. Potthast, M. Hagen, and J. Lin. Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, page 1420–1430. ACM, (July 2024)
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1Report on the Dagstuhl Seminar on Frontiers of Information Access Experimentation for Research and Education
C. Bauer, B. Carterette, N. Ferro, N. Fuhr, J. Beel, T. Breuer, C. Clarke, A. Crescenzi, G. Demartini, G. Di Nunzio and 1 other author(s). ACM SIGIR Forum, 57, page 1--28. ACM New York, NY, USA, (2023)
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1The Information Retrieval Experiment Platform (Extended Abstract)
M. Fröbe, J. Reimer, S. MacAvaney, N. Deckers, J. Bevendorff, B. Stein, M. Hagen, and M. Potthast. Lernen. Wissen. Daten. Analysen. -- LWDA 2023, page 179--191. CEUR-WS.org, (October 2023)
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1The Information Retrieval Experiment Platform (Extended Abstract)
M. Fröbe, J. Reimer, S. MacAvaney, N. Deckers, S. Reich, J. Bevendorff, B. Stein, M. Hagen, and M. Potthast. Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence, page 8405–8410. International Joint Conferences on Artificial Intelligence Organization, (August 2024)
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1Prototyping Open Web Search Applications with TIRA: A Case Study in Research-oriented Teaching
M. Fröbe, T. Elstner, H. Scells, and M. Potthast. 5th International Symposium on Open Search Technology (OSSYM 2023), International Open Search Symposium, (October 2023)
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1Open Web Search at LongEval 2023: Reciprocal Rank Fusion on Automatically Generated Query Variants
M. Fröbe, G. Hendriksen, A. de Vries, and M. Potthast. (2023)
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1Overview of Touché 2024: Argumentation Systems
J. Kiesel, {. Cöltekin, M. Heinrich, M. Fröbe, M. Alshomary, B. De Longueville, T. Erjavec, N. Handke, M. Kopp, N. Ljubesić and 1 other author(s). (2024)
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1Overview of PAN 2024: Multi-author Writing Style Analysis, Multilingual Text Detoxification, Oppositional Thinking Analysis, and Generative AI Authorship Verification Condensed Lab Overview
A. Ayele, N. Babakov, J. Bevendorff, X. Casals, B. Chulvi, D. Dementieva, A. Elnagar, D. Freitag, M. Fröbe, D. Korencić and 1 other author(s). International Conference of the Cross-Language Evaluation Forum for European Languages, page 231--259. Springer, (2024)
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2Resources for Combining Teaching and Research in Information Retrieval Coursework
M. Fröbe, H. Scells, T. Elstner, C. Akiki, L. Gienapp, J. Reimer, S. MacAvaney, B. Stein, M. Hagen, and M. Potthast. Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, page 1115–1125. ACM, (July 2024)
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1The infinite index: Information retrieval on generative text-to-image models
N. Deckers, M. Fröbe, J. Kiesel, G. Pandolfo, C. Schröder, B. Stein, and M. Potthast. Proceedings of the 2023 conference on human information interaction and retrieval, page 172--186. (2023)
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1Evaluating Generative Ad Hoc Information Retrieval
L. Gienapp, H. Scells, N. Deckers, J. Bevendorff, S. Wang, J. Kiesel, S. Syed, M. Fröbe, G. Zuccon, B. Stein and 2 other author(s). Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, page 1916–1929. ACM, (July 2024)
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