Find open-source science resources
A directory of tools, AI models, datasets, and research resources for biotech, bioinformatics, and other scientific fields. Aggregated from curated GitHub awesome-lists, HuggingFace, bio.tools, Bioconductor, and more.
Filters
Health
Domain
Language(1)
License
Source
Type
1,027 of 6,573 resources
Showing 851–900
ChemFIE-SA is a BERT-like sequence classifier for predicting synthesis accessibility given a SELFIES string of a compound, fine-tuned from gbyuvd/chemselfies-base-bertmlm on DeepSA's expanded dataset from Wang et al. 2023.
This model is a BERT-like sequence classifier for 221 human protein drug targets, fine-tuned from gbyuvd/chemselfies-base-bertmlm on a dataset derived ChemBL34 (Zdrazil et al. 2023). It predicts potential drug targets using chemical structures represented as SELFIES (Self-Referencing Embedded…
Resources on ChIP-seq data which include papers, methods, links to software, and analysis.
RaphaelMourad/Mistral-DNA-v1-138M-bacteria
by RaphaelMouradThe Mistral-DNA-v1-138M-bacteria Large Language Model (LLM) is a pretrained generative DNA text model with 17.31M parameters x 8 experts = 138.5M parameters. It is derived from Mistral-7B-v0.1 model, which was simplified for DNA: the number of layers and the hidden size were reduced.
tmberooney/medllama-merged
by tmberooneyModel Card for "medllama" ---------------------------
sagawa/ReactionT5v1-forward
by sagawaThis is a ReactionT5 pre-trained to predict the products of reactions.
Usage-Instructions) - A program to visualize reaction networks.
InstaDeepAI/agro-nucleotide-transformer-1b
by InstaDeepAI## Model Overview AgroNT is a DNA language model trained on primarily edible plant genomes. More specifically, AgroNT uses the transformer architecture with self-attention and a masked language modeling objective to leverage highly available genotype data from 48 different plant speices to learn…
mradermacher/SEMIKONG-70B-v2-GGUF
by mradermacherIf you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.
A benchmarking platform for molecular generation models.
# Medical-Llama3-v2 Fine-Tuned Llama3 for Medical Q&A This repository provides a fine-tuned version of the powerful Llama3 8B model, specifically designed to answer medical questions in an informative way. It leverages the rich knowledge contained in the AI Medical Chatbot dataset…
Diffusion model for scalable protein structure design with multi-motif scaffolding capabilities, achieving state-of-the-art designability, diversity, and novelty through SE(3)-equivariant attention and massive data augmentation (AlQuraishi Lab, 2024)
Partial-Order Alignment for fast alignment and consensus of multiple homologous sequences.
Pangolin is a deep-learning based method for predicting splice site strengths (for details, see Zeng and Li, Genome Biology 2022). It is available as a command-line tool that can be run on a VCF or CSV file containing variants of interest; Pangolin will predict changes in splice site strength due to each variant, and return a file of the same format. Pangolin's models can also be used with custom sequences.
This is an official model checkpoint for Asclepius-Mistral-7B-v0.3 (arxiv). This model is an enhanced version of Asclepius-7B, by replacing the base model with Mistral-7B-v0.3 and increasing the max sequence length to 8192.
This is an official model checkpoint for Asclepius-Llama3-8B (arxiv). This model is an enhanced version of Asclepius-7B, by replacing the base model with Llama-3 and increasing the max sequence length to 8192.
Short Python script (using Biopython library functions) to extract sequences from a FASTA, QUAL, FASTQ, or SFF file based on the list of IDs given by a column of a tabular file. The output order follows that of the tabular file, and if there are duplicates in the tabular file, there will be duplicates in the output sequence file.
Automated data visualization with minimal code
mradermacher/Medichat-V2-Llama3-8B-GGUF
by mradermacherIf you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.
Multi-disciplinary collaboration framework for zero-shot medical reasoning using role-playing LLM agents (ACL 2024)
Henrychur/MMed-Llama-3-8B
by Henrychur# MMedLM 💻Github Repo 🖨️arXiv Paper
nasa-impact/nasa-smd-ibm-st
by nasa-impactThis model is deprecated. please use the updated sentence transformer model here: https://huggingface.co/nasa-impact/nasa-smd-ibm-st-v2. Alternatively, you can also use distilled version of the model here: https://huggingface.co/nasa-impact/nasa-ibm-st.38m
johnsnowlabs/JSL-MedLlama-3-8B-v2.0
by johnsnowlabs# JSL-MedLlama-3-8B-v2.0
Reference: R. Luu and M.J. Buehler, "BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-Inspired Materials," Adv. Science, 2023, DOI: https://doi.org/10.1002/advs.202306724
clinicalnlplab/finetuned-Llama-2-13b-hf-PubmedQA
by clinicalnlplabMedical mT5: An Open-Source Multilingual Text-to-Text LLM for the Medical Domain
# ChemLLM-7B-Chat-1.5-DPO: LLM for Chemistry and Molecule Science ChemLLM-7B-Chat-1.5-DPO, The First Open-source Large Language Model for Chemistry and Molecule Science, Build based on InternLM-2 with ❤
Generative model for programmable protein design using diffusion modeling, equivariant graph neural networks, and conditional random fields to efficiently sample diverse all-atom structures; supports conditional generation via composable conditioners for substructure, symmetry, shape, and neural-network predictions; validated crystallographically (Generate Biomedicines, Nature 2023)
Large-scale PDF/LaTeX/JATS parsing to standardized JSON for millions of papers
[RDKit](http://www.rdkit.org/) and [OSRA](https://cactus.nci.nih.gov/osra/) in the [Bottle](http://bottlepy.org/docs/dev/) on [Tornado](http://www.tornadoweb.org/en/stable/).
!image/png
This model is a fine-tuned version of DeBERTa on the PubMED Dataset.
Circlator is a tool to circularize genome assemblies. It will attempt to identify each circular sequence and output a linearised version of it. It does this by assembling all reads that map to contig ends and comparing the resulting contigs with the input assembly.
Content-Aware Image Restoration for Cryo-Transmission Electron Microscopy Data
MIBiG (Minimum Information about a Biosynthetic Gene Cluster) is a data repository and associated data standard designed to describe biosynthetic gene clusters involved in the production of specialized metabolites. It also stores data on measured biological activities and links to other resources such as NCBI, NPAtlas, and ChEBI. MIBiG is used as a reference database, knowledgebase, and training dataset for machine learning.
file format conversion in Biopython in a convenient way.
Using llama.cpp release b2440 for quantization.
Google DeepMind's AlphaFold-derived classifier for proteome-wide missense variant effect prediction, providing pathogenicity scores for all ~71M possible human missense variants and classifying 89% with 90% precision; pre-computed predictions are integrated into Ensembl VEP and UCSC Genome Browser to support clinical variant interpretation (Science 2023)
Open language model for mathematics (7B/34B) trained on Proof-Pile-2, outperforming Minerva at equal scale on MATH benchmark, with tool use and formal theorem proving in Lean without finetuning (EleutherAI, ICLR 2024)
Goekdeniz-Guelmez/Hyperion-2.0-Mistral-7B-GGUF
by Goekdeniz-Guelmez!image/png
Using llama.cpp commit fa97464 for quantization.
!image/png
# Mr-Grammatology-clinical-problems-Mistral-7B-0.5 !image/png
AlphaPickle is a Python tool that converts AlphaFold and ColabFold output files into user-friendly CSV files and plots, enabling easy analysis and visualization of protein prediction data without requiring programming expertise. It processes .pkl, .json, and PDB files to extract and visualize metrics like pLDDT and PAE.
This is a merge of pre-trained language models created using mergekit.