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
Contrastive VAE models to identify independent disease mechanisms in single-cell data (video )Atanasiu Demian, Harry Rose, Sam Abujudeh, Meltem Gurel
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
Scalable estimation of microbial co-occurrence networks with Variational Autoencoders (video )James Morton, Justin Silverman, Gleb Tigkhonov, Harri Lähdesmäki, Richard Bonneau
Model misspecification is a blessing when estimating fitness from evolutionary sequences (video )Alan Nawzad Amin, Eli N Weinstein, Debora Susan Marks
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
MassFormer: Tandem Mass Spectrum Prediction with Graph Transformers (video )Adamo Young, Bo Wang, Hannes Rost
Inference of pairwise coalescence times and allele ages using deep neural networks Juba Nait Saada, Anthony Hu, Pier Francesco Palamara
Assessing the Impact of Topological Imbalance in Drug Discovery Knowledge Graphs (video )Stephen Bonner, Ufuk Kirik, Ola Engvist, Jian Tang, Ian Barrett
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
grnTea, A Machine Learning Tool to Detect Transposable Element Insertions in Ancient Human Whole Genome Sequencing Data (video )Yilan Wang, Eunjung Alice Lee
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
Embeddings from protein language models predict conservation and variant effects C Marquet, Michael Heinzinger, Tobias Olenyi, Christian Dallago, Kyra Erckert, Michael Bernhofer, Dmitrii Nechaev, Burkhard Rost
CytoImageNet: A large-scale pretraining dataset for bioimage transfer learning (video )Stanley Bryan Zamora Hua, Alex Xijie Lu, Alan Moses
Learning a representation of cellular morphology: unsupervised deep learning for shape and texture characterization of a cell (video )Valentyna Zinchenko, Johannes Hugger, Virginie Uhlmann, Detlev Arendt, Anna Kreshuk
Emphasizing cellular processes by filtering gene expression through projections (video )Zoe Piran, Mor Nitzan
Sparse dictionary learning recovers pleiotropy from human cell fitness screens (video )Joshua Pan, Jason Kwon, Jessica Talamas, Ashir Borah, Francisa Vasquez, Jesse Bohem, Aviad Tsherniak, James McFarland, Marinka Zitnik, William Hahn
A Bayesian nonparametric model for aligning spatial gene expression data (video )
Andrew Jones, F. William Townes, Didong Li, Barbara Engelhardt
Towards data-driven design of context-specific regulatory elements (video )Peter Bromley, Wouter Meuleman
Machine learning for novel antibiotic candidate domains Armi Tiihonen, Sarah J Cox-Vazquez, Guillermo Bazan, Tonio Buonassisi
Enhancing the affinity of protein-protein interactions by multiple amino acid mutations predicted by deep neural networks Reut Moshe, Niv Papo, Yaron Orenstein
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
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
Protein embeddings and deep learning predict binding residues for various ligand classes Maria Littmann, Michael Heinzinger, Christian Dallago, Konstantin Weissenow, Burkhard Rost
Prediction of cell-cell communication directly from scRNA-seq latent spaces (video )Tessa Durakis Green, Linus J Schumacher, Debora Susan Marks, Chris Sander
Contrastive learning on protein embeddings enlightens midnight zone Michael Heinzinger, Maria Littmann, Ian Sillitoe, Nicola Bordin, Christine Orengo
Modeling the Three-Dimensional Chromatin Structure from Hi-C Data with Transfer Learning (video )Tristan Meynier Georges, Marianna Rapsomaniki
Prediction and design of biological sequences combining evolutionary sequence data with sparse labels (video )Ada Shaw, Jung-Eun Shin, Debora Susan Marks
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
Bayesian nonparametric strategies for power maximization in rare variants association studies (video )Lorenzo Masoero, Joshua Schraiber, Tamara Broderick
Towards Remote Protein Homology Detection: Pairwise Alignment Using Locally Enriched Transformer Models Siva Muthupalaniappan, Sean R Eddy, Sam Petti
Protein language model embeddings for fast, accurate, alignment-free protein structure prediction Konstantin Weißenow, Michael Heinzinger, Burkhard Rost
Elucidation of proteasomal cleavage patterns from HLA peptidome data through Deep Learning Emilio Dorigatti, Julian Arnold, Bernd Bischl, Benjamin Schubert
Leveraging Adversarial Reprogramming for Novel Structure-Constrained Protein Sequence Design Devleena Das, Inkit Padhi, Payel Das, Pin-Yu Chen, Amit Dhurandhar
Scaffold Embeddings: Learning the StructureSpanned by Chemical Fragments, Scaffolds andCompounds (video )Austin Clyde, Bharat Kale, Maoyuan Sun, Michael Papka, Arvind Ramanathan, Rick Stevens
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
ProGSNN: Deep Multi-Scale Protein Representation Learning using Geometric Scattering Egbert Castro, Dhananjay Bhaskar, Jackson Grady, Smita Krishnaswamy
Optimal Design of Experiments for Simulation-Based Inference of Mechanistic Acyclic Biological Networks (video )Vincent Zaballa, Elliot Hui
Benchmarking deep generative models for diverse antibody sequence design Igor Melnyk, Payel Das, Vijil Chenthamarakshan, Aurelie Lozano
Rarity: Discovering rare cell populations from single-cell imaging data Kaspar Märtens, Michele Bortolomeazzi, Francesca Ciccarelli, Christopher Yau
Protein Organization with Manifold Exploration and Spectral Clustering Shahab Shams, Geoffroy Dubourg-Felonneau, Eyal Akiva, Lawrence Lee
A Graph Neural Network Approach to Molecule Carcinogenicity Prediction (video )Philip Fradkin, Adamo Young, Lazar Atanackovic, Leo J Lee, Brendan Frey, BO WANG
Deep Unsupervised Learning for Biosynthetic Gene Cluster Detection (video )Carolina Rios-Martinez, Nick Bhattacharya, Ava P. Soleimany, Lorin Crawford, Kevin K Yang
Mapping lineage-traced single-cells across time-points (video )Marius Lange, Zoe Piran, Michal Klein, Fabian J Theis, Mor Nitzan
cov2vec: encoding the genomic manifold of 2+ Million SARS CoV2 viral sequences with protein language models. (video )Salvatore Loguercio
Organ Source Prediction for Exosomal Proteomics via Protein Language Models Xinbo Wu, Alexandru Hanganu, Ayuko Hoshino, Lav R. Varshney
Self-Supervised Vision Transformers Learn Disentangled Representations in Histopathology Richard J. Chen, Rahul G Krishnan
Modeling gene regulatory network dynamics through graph embedding alignment (video )Hao Chen, Xiong Liu, Joseph Xu Zhou
Joint embedding of sequence features (texts) and function labels (graphs) for protein function prediction Yue Cao, Yang Shen
Deep generative modeling of transcription factor–gene expression relationships Byunguk Kang, Daniel Y. Zhu, William Souillard-Mandar, Hattie Chung, Fei Chen
AugmentedPCA: A Python Package of Supervised and Adversarial Linear Factor Models William E Carson IV, Austin Talbot, David Carlson
Bidirection Prediction Model for Transcriptomics and Proteomics Tianyu Liu, Yuge Wang, Hongyu Zhao
Improvising the Learning of Neural Networks on Hyperspherical Manifold Lalith Bharadwaj Baru, Sai Vardhan Kanumolu, Shilhora Akshay, Madhu G
Emergence of Division of Labor in Tissues through Cell Interactions and Spatial Cues
(video )
Miri Adler, Noa Moriel, Aleksandrina Goeva, Evan Macosko, Aviv Regev, Ruslam Medzhitov, Mor Nitzan