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Workshop

Learning Meaningful Representations of Life

Elizabeth Wood ⋅ Adji Bousso Dieng ⋅ Aleksandrina Goeva ⋅ Alex X Lu ⋅ Anshul Kundaje ⋅ Chang Liu ⋅ Debora Marks ⋅ Ed Boyden ⋅ Eli N Weinstein ⋅ Lorin Crawford ⋅ Mor Nitzan ⋅ Rebecca Boiarsky ⋅ Romain Lopez ⋅ Tamara Broderick ⋅ Ray Jones ⋅ Wouter Boomsma ⋅ Yixin Wang ⋅ Stephen Ra
Project Page [ Contact: lmrl@lmrl.org ]

Abstract

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Schedule

Timezone: America/Los_Angeles
5:00 AM
Keynote - Rich Bonneau
Richard Bonneau
7:00 AM
Poster Session
8:00 AM
Keynote - Shantanu Singh
Shantanu Singh
1:00 PM
Poster Session
A generative recommender system with GMM prior for cancer drug generation and sensitivity prediction
Krzysztof Koras ⋅ Marcin Możejko ⋅ Paulina Szymczak ⋅ Adam Izdebski ⋅ Eike Staub ⋅ Ewa Szczurek
Energy-based Modelling for Single-cell Data Annotation
Tianyi Liu ⋅ Philip Fradkin ⋅ Lazar Atanackovic ⋅ Leo J Lee
Modeling Single-Cell Dynamics Using Unbalanced Parameterized Monge Maps
Luca Eyring ⋅ Dominik Klein ⋅ Giovanni Palla ⋅ Sören Becker ⋅ Philipp Weiler ⋅ Niki Kilbertus ⋅ Fabian Theis
Biological Cartography: Building and Benchmarking Representations of Life
Safiye Celik ⋅ Jan-Christian Huetter ⋅ Sandra Melo ⋅ Nathan Lazar ⋅ Rahul Mohan ⋅ Conor Tillinghast ⋅ Tommaso Biancalani ⋅ Marta Fay ⋅ Berton Earnshaw ⋅ Imran Haque
Designing active and thermostable enzymes with sequence-only predictive models
Clara Fannjiang ⋅ Micah Olivas ⋅ Eric Greene ⋅ Craig Markin ⋅ Bram Wallace ⋅ Ben Krause ⋅ Margaux Pinney ⋅ James Fraser ⋅ Polly Fordyce ⋅ Ali Madani ⋅ Nikhil Naik
Interpretable visualization of single cell data using Janus autoencoders
Gokul Gowri ⋅ Phillipa Richter ⋅ Xiaokang Lun ⋅ Peng Yin
Machine Learning enabled Pooled Optical Screening in Human Lung Cancer Cells
Srinivasan Sivanandan ⋅ Max Salick ⋅ Bobby Leitmann ⋅ Kara Liu ⋅ Navpreet Ranu ⋅ Cynthia Hao ⋅ Owen Chen ⋅ John Bisognano ⋅ Eric Lubeck ⋅ Ajamete Kaykas ⋅ Eilon Sharon ⋅ Ci Chu
An Empirical Study of ML-based Phenotyping and Denoising for Improved Genomic Discovery
Bo Yuan ⋅ Cory McLean ⋅ Farhad Hormozdiari ⋅ Justin Cosentino
Find your microenvironments faster with Neural Spatial LDA
Sivaramakrishnan Sankarapandian ⋅ Zhenghao Chen ⋅ Jun Xu
TranceptEVE: Combining Family-specific and Family-agnostic Models of Protein Sequences for Improved Fitness Prediction
Pascal Notin ⋅ Lodevicus van Niekerk ⋅ Aaron Kollasch ⋅ Daniel Ritter ⋅ Yarin Gal ⋅ Debora Marks
Tuned Quadratic Landscapes for Benchmarking Model-Guided Protein Design
Neil Thomas ⋅ Atish Agarwala ⋅ David Belanger ⋅ Yun Song ⋅ Lucy Colwell
Neural Unbalanced Optimal Transport via Cycle-Consistent Semi-Couplings
Frederike Lübeck ⋅ Charlotte Bunne ⋅ Gabriele Gut ⋅ Jacobo Sarabia del Castillo ⋅ Lucas Pelkmans ⋅ David Alvarez-Melis
ChromFormer: A transformer-based model for 3D genome structure prediction
Henry Valeyre ⋅ Pushpak Pati ⋅ Federico Gossi ⋅ Vignesh Ram Somnath ⋅ Adriano Martinelli ⋅ Maria Anna Rapsomaniki
Improving Protein Subcellular Localization Prediction with Structural Prediction & Graph Neural Networks
Geoffroy Dubourg-Felonneau ⋅ Arash Abbasi ⋅ Eyal Akiva ⋅ Lawrence Lee
A single-cell gene expression language model
William Connell ⋅ Umair Khan ⋅ Michael Keiser
Standards, tooling and benchmarks to probe representation learning on proteins
Joaquin Gomez Sanchez ⋅ Sebastian Franz ⋅ Michael Heinzinger ⋅ Burkhard Rost ⋅ Christian Dallago
CP2Image: generating high-quality single-cell images using CellProfiler representations
Yanni Ji ⋅ Marie Cutiongco ⋅ Bjørn S Jensen ⋅ Ke Yuan
Knowledge distillation for fast and accurate DNA sequence correction
Anastasiya Belyaeva ⋅ Joel Shor ⋅ Daniel Cook ⋅ Kishwar Shafin ⋅ Daniel Liu ⋅ Armin Töpfer ⋅ Aaron Wenger ⋅ William Rowell ⋅ Howard Yang ⋅ Alexey Kolesnikov ⋅ Cory McLean ⋅ Maria Nattestad ⋅ Andrew Carroll ⋅ Pi-Chuan Chang
meTCRs - Learning a metric for T-cell receptors
Felix Drost ⋅ Lennard Schiefelbein ⋅ Benjamin Schubert
Is brightfield all you need for MoA prediction?
Ankit Gupta ⋅ Philip Harrison ⋅ Håkan Wieslander ⋅ Jonne Rietdijk ⋅ Jordi Puigvert ⋅ Polina Georgiev ⋅ Carolina Wählby ⋅ Ola Spjuth ⋅ Ida-Maria Sintorn
MolE: a molecular foundation model for drug discovery
Oscar Méndez-Lucio ⋅ Christos Nicolaou ⋅ Berton Earnshaw
Learning representations of cell populations for image-based profiling using contrastive learning
Robert van Dijk ⋅ John Arevalo ⋅ Shantanu Singh ⋅ Anne Carpenter
Forecasting labels under distribution-shift for machine-guided sequence design
Lauren B Wheelock ⋅ Stephen Malina ⋅ Jeffrey Gerold ⋅ Sam Sinai
decOM: Similarity-based microbial source tracking of ancient oral samples using k-mer-based methods
Camila Duitama González ⋅ Riccardo Vicedomini ⋅ Teo Lemane ⋅ Nicolas Rascovan ⋅ Hugues Richard ⋅ Rayan Chikhi
Transformer Model for Genome Sequence Analysis
Noah Hurmer ⋅ Xiao-Yin To ⋅ Martin Binder ⋅ Hüseyin Anil Gündüz ⋅ Philipp Münch ⋅ René Mreches ⋅ Alice McHardy ⋅ Bernd Bischl ⋅ Mina Rezaei
SCOOTR: Single-Cell Multimodal Data Integration with Contrastive Learning and Optimal Transport
Federico Gossi ⋅ Pushpak Pati ⋅ Adriano Martinelli ⋅ Maria Anna Rapsomaniki
Conditional Neural Processes for Molecules
Miguel Garcia-Ortegon ⋅ Andreas Bender ⋅ Sergio Bacallado
Fuzzy Logic for Biological Networks as ML Regression: Scaling to Single-Cell Datasets With Autograd
Constance LE GAC ⋅ Alice Driessen ⋅ Nicolas Deutschmann ⋅ Maria Rodriguez Martinez
Seeded iterative clustering for histology region identification
Eduard Artur Chelebian Kocharyan ⋅ Francesco Ciompi ⋅ Carolina Wählby
Learning relationships between histone modifications in single cells
Jake Yeung ⋅ Maria Florescu ⋅ Peter Zeller ⋅ Buys de Barbanson ⋅ Max Wellenstein ⋅ Alexander van Oudenaarden
Data-driven subgroup identification for linear regression
Zachary Izzo ⋅ Ruishan Liu ⋅ James Zou
Deep Fitness Inference for Drug Discovery with Directed Evolution
Nathaniel Diamant ⋅ Ziqing Lu ⋅ Christina Helmling ⋅ Kangway Chuang ⋅ Christian Cunningham ⋅ Tommaso Biancalani ⋅ Gabriele Scalia ⋅ Max Shen
Using hierarchical variational autoencoders to incorporate conditional independent priors for paired single-cell multi-omics data integration
Ping-Han Hsieh ⋅ Ru-Xiu Hsiao ⋅ Tatiana Belova ⋅ Katalin Ferenc ⋅ Anthony Mathelier ⋅ Rebekka Burkholz ⋅ Chien-Yu Chen ⋅ Geir Kjetil Sandve ⋅ Marieke L Kuijjer
3D single-cell shape analysis of cancer cells using geometric deep learning
Matt De Vries ⋅ Lucas Dent ⋅ Nathan Curry ⋅ Leo Rowe-Brown ⋅ Adam Tyson ⋅ Chris Dunsby ⋅ Chris Bakal
Kernelized Stein Discrepancies for Biological Sequences
Alan Amin ⋅ Eli Weinstein ⋅ Debora Marks
scPerturb: Information Resource for Harmonized Single-Cell Perturbation Data
Tessa Green ⋅ Stefan Peidli ⋅ Ciyue Shen ⋅ Torsten Gross ⋅ Joseph Min ⋅ Samuele Garda ⋅ Jake Taylor-King ⋅ Debora Marks ⋅ Augustin Luna ⋅ Nils Blüthgen ⋅ Chris Sander
Utilizing Mutations to Evaluate Interpretability of Neural Networks on Genomic Data
Utku Ozbulak ⋅ Solha Kang ⋅ Jasper Zuallaert ⋅ Stephen Depuydt ⋅ Joris Vankerschaver
Unsupervised language models for disease variant prediction
Allan Zhou ⋅ Nicholas C. Landolfi ⋅ Daniel ONeill
Spatially-aware dimension reduction of transcriptomics data
Lauren Okamoto ⋅ Andrew Jones ⋅ Archit Verma ⋅ Barbara E Engelhardt
Multimodal deep transfer learning for the analysis of optical coherence tomography scans and retinal fundus photographs
Zoi Tsangalidou ⋅ Edwin Fong ⋅ Josefine Vilsbøll Sundgaard ⋅ Trine J Abrahamsen ⋅ Kajsa Kvist
Designing and Evolving Neuron-Specific Proteases
Han Spinner ⋅ Colin Hemez ⋅ Julia McCreary ⋅ David Liu ⋅ Debora Marks
Network-Based Clustering of Pan-Cancer Data Accounting for Clinical Covariates
Fritz Bayer ⋅ Giusi Moffa ⋅ Niko Beerenwinkel ⋅ Jack Kuipers
CoSpar identifies early cell fate biases from single cell transcriptomic and lineage information
Shou-Wen Wang ⋅ Michael Herriges ⋅ Kilian Hurley ⋅ Darrell Kotton
What cleaves? Is proteasomal cleavage prediction reaching a ceiling?
Ingo Ziegler ⋅ Bolei Ma ⋅ Ercong Nie ⋅ Bernd Bischl ⋅ David Rügamer ⋅ Benjamin Schubert ⋅ Emilio Dorigatti
Learning More Effective Cell Representations Efficiently
Jason Xiaotian Dou ⋅ Minxue Jia ⋅ Nika Zaslavsky ⋅ Haiyi Mao ⋅ Runxue Bao ⋅ Ni Ke ⋅ Paul Pu Liang ⋅ Zhi-Hong Mao
Biological Neurons vs Deep Reinforcement Learning: Sample efficiency in a simulated game-world
Forough Habibollahi ⋅ Moein Khajehnejad ⋅ Amitesh Gaurav ⋅ Brett J. Kagan
Self-Supervised Learning of Phenotypic Representations from Cell Images with Weak Labels
Jan Cross-Zamirski ⋅ Guy Williams ⋅ Elizabeth Mouchet ⋅ Carola-Bibiane Schönlieb ⋅ Riku Turkki ⋅ Yinhai Wang