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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.
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11 of 6,573 resources
Toolbox for comparative genomics of MAGs
Rapid & standardized annotation of bacterial genomes, MAGs & plasmids
The application of 2nd and 3rd generation High Throughput Sequencing (HTS) technologies has deeply reshaped experimental method to investigate microbial communities and obtain a taxonomic and functional profile of the invetigated community. Shotgun Metagenomics allow to quickly obtain a representation of microorganisms genomes characterizing a particular environment. In order to obtain a fast e reliable taxonomic classification of microorganisms genomes we present kMetaShot, an alignment-free taxonomic classifier based on k-mer/minimizer counting.
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.
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.
NuclearPhaser is a method for phasing of dikaryotic genomes into the two haplotypes using Hi-C contact graphs. This is an overview of the phasing pipeline for dikaryons.
Filtering and trimming of long read sequencing data.
qam is a Python library and command-line tool to compute 3D surface-distances for evaluating liver ablation/tumor completeness based on segmentation images.
Prediction of mRNA subcellular localization using deep recurrent neural networks | RNATracker is a deep learning approach to learn mRNA subcellular localization patterns and to infer its outcome. It operates on the cDNA of the longest isoformic protein-coding transcript of a gene with or without its corresponding secondary structure annnotations. The learning targets are fractions/percentage of the transcripts being localized to a fixed set of subcellular compartments of interest
CompuCell3D is a multiscale multicellular virtual tissue modeling and simulation environment. CompuCell3D is written in C++ and provides Python bindings for model and simulation development in Python.
metagWGS is a workflow dedicated to the analysis of metagenomic data. It allows assembly, taxonomic annotation, and functional annotation of predicted genes. Since release 2.3, binning step with the possibility of cross-alignment is included. It has been developed in collaboration with several CATI BIOS4biol agents. Funded by Antiselfish Project (Labex Ecofect), ExpoMicoPig project (France Futur elevage) and SeqOccIn project (CPER - Occitanie Toulouse / FEDER), ATB_Biofilm funded by PNREST Anses, France genomique (ANR-10-INBS-09-08) and Resalab Ouest.