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natural language descriptions of protein functions from amino acid sequences.

This repository contains the PyTorch model weights for MarS-FM

protein-language generative model — because proteins deserve better small talk

UBio-MolFM is a foundation model suite for molecular modeling

protein-conditioned codon sequence generation model trained on the representative

protein-language generative model — because proteins deserve better small talk

🧬 BioReason-ProAdvancing Protein Function Prediction withMultimodal Biological Reasoning

🧬 BioReason-ProAdvancing Protein Function Prediction withMultimodal Biological Reasoning

EVA is a generative foundation model for universal RNA modeling

- This repository contains code to utilize the model, and reproduce

protein language model distilled from ProtGPT2 using complementary-regularizer distillation

protein language model distilled from ProtGPT2 using complementary-regularizer distillation

protein language model distilled from ProtGPT2 using complementary-regularizer distillation

# ibm/biomed.sm.mv-te-84m-MoleculeNet-ligand_scaffold-BACE-101 biomed.sm.mv-te-84m is a multimodal biomedical foundation model

# ibm-research/biomed.sm.mv-te-84m biomed.sm.mv-te-84m is a multimodal biomedical

State-of-the-Art Geometric GNN for Predicting Molecular Properties

TM-Vec 2: Transformer-based architecture for remote homology detection

MACE-MH-1 is a foundation machine-learning interatomic potential

Distributed and Parallel Molecular Docking Platform

protein embeddings for 236,252 human proteins using ESMC models

This model is a lightweight model pre-trained on SELFIES

> [!NOTE] > This model has been optimized using NVIDIA

> [!NOTE] > This model has been optimized using NVIDIA

protein structures, presented in the paper JAMUN: Bridging Smoothed Molecular

# Model details ## Model description Nature Language Model (NatureLM) is a

# Model details ## Model description Nature Language Model (NatureLM) is a

protein function prediction from amino acid sequences using the Gene

protein function prediction from amino acid sequences using the Gene

protein function prediction from amino acid sequences using the Gene

protein function prediction from amino acid sequences using the Gene

protein function prediction from amino acid sequences using the Gene

protein function prediction from amino acid sequences using the Gene

protein. This is an example for finetuning ibm/biomed.omics.bl.sm-ted-458m for protein

View label scheme (20 labels for 1 components)

Prediction and Designing of thermostable proteins with a desired melting temperature

INDUS-Retriever-small (previously nasa-smd-ibm-st.38m) is

Accurate prediction of drug-target binding affinity is essential in

Drugs must satisfy stringent criteria for both efficacy and safety

Drugs must satisfy stringent criteria for both efficacy and safety

Drugs targeting the central nervous system must meet stringent criteria

Accurate prediction of drug-target binding affinity is essential in

proteins, small molecules, and single-cell gene data. Designed for robust

protein phenotypes, which combines a large language model with protein

Boltz-1:

# ibm/biomed.sm.mv-te-84m-MoleculeNet-ligand_scaffold-HIV-101 biomed.sm.mv-te-84m is a multimodal biomedical foundation model

# ibm/biomed.sm.mv-te-84m-MoleculeNet-ligand_scaffold-FREESOLV-101 biomed.sm.mv-te-84m is a multimodal biomedical foundation model

# ibm/biomed.sm.mv-te-84m-MoleculeNet-ligand_scaffold-QM7-101 biomed.sm.mv-te-84m is a multimodal biomedical foundation model

# ibm/biomed.sm.mv-te-84m-MoleculeNet-ligand_scaffold-BBBP-101 biomed.sm.mv-te-84m is a multimodal biomedical foundation model

# ibm/biomed.sm.mv-te-84m-MoleculeNet-ligand_scaffold-ESOL-101 biomed.sm.mv-te-84m is a multimodal biomedical foundation model

# ibm/biomed.sm.mv-te-84m-MoleculeNet-ligand_scaffold-CLINTOX-101 biomed.sm.mv-te-84m is a multimodal biomedical foundation model