KGARevion
Knowledge Graph Based Agent for Complex, Knowledge-Intensive QA in Medicine
PocketFlow
Generalized Protein Pocket Generation with Prior-Informed Flow Matching
Therapeutics Data Commons 2.0
Multimodal Foundation for Therapeutic Science
SPECTRA
Evaluating Generalizability of Artificial Intelligence Models for Molecular Datasets
PDGrapher
Combinatorial Prediction of Therapeutic Perturbations Using Causally-Inspired Neural Networks
TxGNN
A Foundation Model for Clinician Centered Drug Repurposing
TimeX
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency
Raincoat
Domain Adaptation for Time Series Under Feature and Label Shifts
SHEPHERD
Deep Learning for Diagnosing Patients with Rare Genetic Diseases
metapaths
Similarity Search in Heterogeneous Knowledge Graphs via Meta Paths
Mutual Interactors
Phenotype Discovery in Molecular Interaction Networks
Raindrop
Graph-Guided Network for Irregularly Sampled Multivariate Time Series
Therapeutics Data Commons
Machine Learning Datasets and Tasks for Drug Discovery and Development
DeepPurpose
Deep learning library for drug-target interaction prediction and applications to drug repurposing and virtual screening
Graph Query Embeddings
Method for embedding logical queries on knowledge graphs
Network-Guided Matrix Completion
Method for probabilistic prediction and imputation of interactions using prior knowledge
Multi-BioNER
Deep multi-task learning for cross-type biomedical named entity recognition
Latest News
Nov 2024: Biomedical AI Agents in Cell
Oct 2024: Activity Cliffs in Molecular Property Prediction
Oct 2024: Knowledge Graph Agent for Medical Reasoning
New paper introducing a knowledge graph agent for complex, knowledge-intensive medical reasoning.
Sep 2024: Three Papers Accepted to NeurIPS
Exciting projects include a unified multi-task time series model, a flow-matching approach for generating protein pockets using geometric priors, and a tokenization method that produces invariant molecular representations for integration into large language models.
Sep 2024: TxGNN Published in Nature Medicine
Graph foundation model for drug repurposing published in Nature Medicine. [Harvard Gazette] [Harvard Medicine News] [Forbes] [NVIDIA]
Aug 2024: Graph AI in Medicine
Excited to share a new perspective on Graph Artificial Intelligence in Medicine in Annual Reviews.
Aug 2024: How Proteins Behave in Context
Harvard Medicine News on our new AI tool that captures how proteins behave in context. Kempner Institute on how context matters for foundation models in biology.
Jul 2024: PINNACLE in Nature Methods
PINNACLE contextual AI model is published in Nature Methods. Paper. Research Briefing. Project website.
Jul 2024: Digital Twins as Global Health and Disease Models of Individuals
Paper on digitial twins outlining strategies to leverage molecular and computational techniques to construct dynamic digital twins on the scale of populations to individuals.
Jul 2024: Graph Diffusion Convolutions at ICML
Graph diffusion convolution is a geometric deep learning architecture that aggregates information from higher-order network neighbors through a generalized graph diffusion to enhance model robustness to noisy and incomplete datasets. Paper at ICML.
Jul 2024: Three Papers: TrialBench, 3D Structure Design, LLM Editing
Jun 2024: TDC-2: Multimodal Foundation for Therapeutics
The Commons 2.0 (TDC-2) is an overhaul of Therapeutic Data Commons to catalyze research in multimodal models for drug discovery by unifying single-cell biology of diseases, biochemistry of molecules, and effects of drugs through multimodal datasets, AI-powered API endpoints, new tasks and benchmarks. Our paper.
May 2024: Broad MIA: Protein Language Models
Check out our Broad’s seminars on Multimodal protein language models for deciphering protein function.
May 2024: On Knowing a Gene in Cell Systems
Apr 2024: Biomedical AI Agents
We envision ‘AI scientists’ as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate machine learning tools with experimental platforms.
Mar 2024: Efficient ML Seminar Series
We started a Harvard University Efficient ML Seminar Series. Congrats to Jonathan for spearheading this initiative. Harvard Magazine covered the first meeting focusing on LLMs.
Mar 2024: UniTS - Unified Time Series Model
UniTS is a unified time series model that can process classification, forecasting, anomaly detection and imputation tasks within a single model with no task-specific modules. UniTS has zero-shot, few-shot, and prompt learning capabilities. Project website.
Mar 2024: Weintraub Graduate Student Award
Michelle receives the 2024 Harold M. Weintraub Graduate Student Award. The award recognizes exceptional achievement in graduate studies in biological sciences. News Story. Congratulations!
Mar 2024: PocketGen - Generating Full-Atom Ligand-Binding Protein Pockets
PocketGen is a deep generative model that generates residue sequence and full-atom structure of protein pockets, maximizing binding to ligands. Project website.
Feb 2024: SPECTRA - Generalizability of Molecular AI
SPECTRA is an approach for holistic evaluation of how AI models generalize to new molecular datasets. Project website.
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