-
University of Toronto
- Toronto
-
13:46
(UTC -05:00) - https://rexxxx1234.github.io/
- @RexMa9
- in/rex-ma-20a455113
Stars
BioReason: Incentivizing Multimodal Biological Reasoning within a DNA-LLM Model
Comprehensive suite for evaluating perturbation prediction models
scplode: A memory-efficient and fast accessor of single cell adata files
A partially latent flow matching model for the joint generation of a protein’s amino acid sequence and full atomistic structure, including both the backbone and side chain.
RNAtranslator: Modeling protein-conditional RNA design as sequence-to-sequence natural language translation
A modern chat interface for AI agents built with Next.js, Tailwind CSS, and TypeScript.
Agent-R1: Training Powerful LLM Agents with End-to-End Reinforcement Learning
Fitness landscape exploration sandbox for biological sequence design.
gpt-oss-120b and gpt-oss-20b are two open-weight language models by OpenAI
H-Net: Hierarchical Network with Dynamic Chunking
Protein Engineering via Exploration of an Energy Landscape
AIDO.ModelGenerator is a software stack powering the development of an AI-driven Digital Organism (AIDO) by enabling researchers to adapt pretrained models and generate finetuned models for downstr…
Benchmark gene representations from different model families
Chai-1, SOTA model for biomolecular structure prediction
DockQ is a single continuous quality measure for Protein, Nucleic Acids and Small Molecule Docking Models
Repository for "NucleoBench: A Large-Scale Benchmark of Neural Nucleic Acid Design Algorithms"
RNAGenesis: A Generalist Foundation Model for Functional RNA Therapeutics
RiboNN: predicting translation efficiencies from mRNA sequences
This repository delivers end-to-end, code-first tutorials covering every layer of production-grade GenAI agents, guiding you from spark to scale with proven patterns and reusable blueprints for re…
OctoTools: An agentic framework with extensible tools for complex reasoning
Official implementation for the paper "Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning"