| 1 |
A |
Assessing the importance of diagnostic information in learning low-dimensional embedding of high-dimensional abnormal neural correlates |
Wenjun Bai, Tomoki Tokuda, Okito Yamashita, Junichiro Yoshimoto |
| 2 |
A |
Protein embeddings and deep learning predict binding residues for various ligand classes |
Maria Littmann, Michael Heinzinger, Christian Dallago, Konstantin Weissenow, Burkhard Rost |
| 3 |
A |
Optimal Design of Stochastic DNA Synthesis Protocols Based on Generative Sequence Models (video) |
Eli N Weinstein, Alan Nawzad Amin, Will Sussman Grathwohl, Daniel Kassler, Jean Disset, Debora Susan Marks |
| 4 |
A |
Benchmarking deep generative models for diverse antibody sequence design |
Igor Melnyk, Payel Das, Vijil Chenthamarakshan, Aurelie Lozano |
| 5 |
A |
Scalable estimation of microbial co-occurrence networks with Variational Autoencoders (video) |
James Morton, Justin Silverman, Gleb Tikhonov, Harri Lähdesmäki, Richard Bonneau |
| 6 |
A |
CytoImageNet: A large-scale pretraining dataset for bioimage transfer learning (video) |
Stanley Bryan Zamora Hua, Alex Xijie Lu, Alan Moses |
| 7 |
A |
Elucidation of proteasomal cleavage patterns from HLA peptidome data through deep learning |
Emilio Dorigatti, Julian Arnold, Bernd Bischl, Benjamin Schubert |
| 8 |
A |
Bidirection Prediction Model for Transcriptomics and Proteomics |
Tianyu Liu, Yuge Wang, Hongyu Zhao |
| 9 |
A |
AugmentedPCA: A Python Package of Supervised and Adversarial Linear Factor Models |
William E Carson IV, Austin Talbot, David Carlson |
| 10 |
A |
A Graph Neural Network Approach to Molecule Carcinogenicity Prediction (video) |
Philip Fradkin, Adamo Young, Lazar Atanackovic, Leo J Lee, Brendan Frey, BO WANG |
| 11 |
A |
Organ Source Prediction for Exosomal Proteomics via Protein Language Models |
Xinbo Wu, Alexandru Hanganu, Ayuko Hoshino, Lav R. Varshney |
| 12 |
A |
Enhancing the affinity of protein-protein interactions by multiple amino acid mutations predicted by deep neural networks |
Reut Moshe, Niv Papo, Yaron Orenstein |
| 13 |
A |
Towards data-driven design of context-specific regulatory elements (video) |
Peter Bromley, Wouter Meuleman |
| 14 |
A |
Learning a representation of cellular morphology: unsupervised deep learning for shape and texture characterization of cells in EM data (video) |
Valentyna Zinchenko, Johannes Hugger, Virginie Uhlmann, Detlev Arendt, Anna Kreshuk |
| 15 |
A |
Machine learning for novel antibiotic candidate domains - conjugated oligoelectrolytes |
Armi Tiihonen, Sarah J Cox-Vazquez, Guillermo Bazan, Tonio Buonassisi |
| 16 |
A |
Bayesian nonparametric strategies for power maximization in rare variants association studies (video) |
Lorenzo Masoero, Joshua Schraiber, Tamara Broderick |
| 17 |
B |
Deep Generative Modeling of Transcription Factor-Gene Expression Relationships |
Byunguk Kang, Daniel Y. Zhu, William Souillard-Mandar, Hattie Chung, Fei Chen |
| 18 |
B |
TeraTox empowers preclinical teratogenicity assessment with stem cells, sequencing, and explainable machine learning (video) |
Jitao David Zhang, Manuela Jaklin, Nicole Schäfer, Nicole Clemann, Paul Barrow, Erich Küng, Lisa Sach-Peltason, Claudia McGinnis, Marcel Leist, Stefan Kustermann |
| 19 |
B |
Optimal Design of Experiments for Simulation Based Inference of Mechanistic Acyclic Biological Networks (video) |
Vincent Zaballa, Elliot Hui |
| 20 |
B |
Protein Organization with Manifold Exploration and Spectral Clustering |
Shahab Shams, Geoffroy Dubourg-Felonneau, Eyal Akiva, Lawrence Lee |
| 21 |
B |
Towards Remote Protein Homology Detection: Pairwise Alignment Using Locally Enriched Transformers |
Siva Muthupalaniappan, Sean R Eddy, Sam Petti |
| 22 |
B |
A Bayesian nonparametric model for aligning spatial gene expression data (video) |
Andrew Jones, F. William Townes, Didong Li, Barbara Engelhardt |
| 23 |
B |
Leveraging Adversarial Reprogramming for Template-Constrained Protein Sequence Design |
Devleena Das, Inkit Padhi, Payel Das, Pin-Yu Chen, Amit Dhurandhar |
| 24 |
C |
Deep Unsupervised Learning for Biosynthetic Gene Cluster Characterization (video) |
Carolina Rios-Martinez, Nick Bhattacharya, Ava P. Soleimany, Lorin Crawford, Kevin K Yang |
| 25 |
B |
Prediction of cell-cell communication directly from scRNA-seq latent spaces (video) |
Tessa Durakis Green, Linus J Schumacher, Debora Susan Marks, Chris Sander |
| 26 |
B |
InterDocker: End-to-End Cross-Attentive and Geometric Transformers for Efficient Iterative Protein Docking |
Allan Dos Santos Costa, Manvitha Ponnapati, Eric Alcaide, Kalyan Palepu, Suhaas M Bhat, Pranam Chaterjee, JOSEPH JACOBSON, Iddo Drori |
| 27 |
B |
Prediction and design of biological sequences combining evolutionary sequence data with sparse labels (video) |
Ada Shaw, Jung-Eun Shin, Debora Susan Marks |
| 28 |
B |
Modeling gene regulatory network dynamics in tumor through graph embedding alignment (video) |
Hao Chen, Xiong Liu, Joseph Xu Zhou |
| 29 |
B |
ProGSNN: Deep Multi-Scale Protein Representation Learning using Geometric Scattering |
Egbert Castro, Dhananjay Bhaskar, Jackson Grady, Smita Krishnaswamy |
| 30 |
B |
cov2vec: encoding the genomic manifold of 2+ million SARS CoV2 viral sequences with protein language models. (video) |
Salvatore Loguercio |
| 31 |
B |
Protein language model embeddings for fast, accurate, alignment-free protein structure prediction |
Konstantin Weißenow, Michael Heinzinger, Burkhard Rost |
| 32 |
B |
A generative model of the human proteome using across-species and within-species sequence data |
Jonathan Frazer, Mafalda Dias, Rose Orenbuch, Nikki Thadani, Kelly Brock |
| 33 |
C |
MassFormer: Tandem Mass Spectrum Prediction with Graph Transformers (video) |
Adamo Young, Bo Wang, Hannes Röst |
| 34 |
C |
Prediction of cell-cell communication in scRNA-seq latent spaces (video) |
Tessa Durakis Green, Linus J Schumacher, Debora Susan Marks, Chris Sander |
| 35 |
C |
Similarity Neural Networks for RBP Binding Site Detection |
Sepideh Saran, Mahsa Ghanbari, Uwe Ohler |
| 36 |
C |
Joint embedding of sequence features (texts) and function labels (graphs) for protein function prediction |
Yue Cao, Yang Shen |
| 37 |
C |
Self-Supervised Vision Transformers Learn Disentangled Representations in Histopathology |
Richard J. Chen, Rahul G Krishnan |
| 38 |
C |
Contrastive VAE models to identify independent disease mechanisms in single-cell data (video) |
Atanasiu Demian, Harry Rose, Sam Abujudeh, Meltem Gurel |
| 39 |
C |
Benchmarking algorithms to identify clinically-relevant sub-populations of patients (video) |
Manuela Salvucci, Meltem Gürel, Sam Abujudeh, Marika Catapano, Gregor Lueg, Matyas Korom, Manav Leslie, Peter McErlean, Francesca Mulas |
| 40 |
C |
Interpretable graph representation learning for lectin-glycan binding (video) |
Joyce An, Somesh Mohapatra, Omar A Santiago-Reyes, Daria E Kim, Laura Kiessling, Rafael Gomez-Bombarelli |
| 41 |
C |
Vaccine Design using Machine Learning of Human Degrons (video) |
Somesh Mohapatra, Nicholas L Truex, Mariane Bandeira Melo, Na Li, Wuhbet D Abraham, Jacob Joshua Lee Rodriguez, Darrell J Irvine, Bradley Pentelute, Rafael Gomez-Bombarelli |
| 42 |
C |
Mapping Biology With a Unified Representation Space for Genomic and Chemical Perturbations to Enable Accelerated Drug Discovery (video) |
Aurora S Blucher, Safiye Celik, James Douglas Jensen, James Taylor, Michael F Cuccarese, Jacob C Cooper, Jacob M Rinaldi, Carl Brooks, Michael A Statnick, Marta Fay, Nathan Lazar, Berton Earnshaw, Imran S Haque |
| 43 |
C |
Simultaneous CUT&Tag profiling of the accessible and silenced regulome in single cells (video) |
Derek H. Janssens, Dominik Jenz Otto, Michael P. Meers, Kami Ahmad, Manu Setty, Steven Henikoff |
| 44 |
C |
Rarity: a framework for the discovery of putative rare cell populations from single-cell imaging data |
Kaspar Märtens, Michele Bortolomeazzi, Francesca Ciccarelli, Christopher Yau |