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Skills IA databases bioinformatics

Découvrez les skills databases bioinformatics, comparez leurs dépôts et consultez leurs instructions.

Catégories: databases bioinformatics

697–720 sur 920

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Explorer

GitHub

deepchem

hxk622

Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks....

GitHub

string-database

hxk622

Query STRING API for protein-protein interactions (59M proteins, 20B interactions). Network analysis, GO/KEGG enrichment, interaction discovery, 5000+ species, for systems biology.

GitHub

biomni

hxk622

Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical rese...

GitHub

uniprot-database

hxk622

Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use thi...

GitHub

denario

hxk622

Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing re...

GitHub

biopython

hxk622

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioin...

GitHub

hmdb-database

hxk622

Access Human Metabolome Database (220K+ metabolites). Search by name/ID/structure, retrieve chemical properties, biomarker data, NMR/MS spectra, pathways, for metabolomics and identification.

GitHub

cosmic-database

hxk622

Access COSMIC cancer mutation database. Query somatic mutations, Cancer Gene Census, mutational signatures, gene fusions, for cancer research and precision oncology. Requires authentication.

GitHub

esm

hxk622

Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use...

GitHub

rowan

hxk622

Cloud-based quantum chemistry platform with Python API. Preferred for computational chemistry workflows including pKa prediction, geometry optimization, conformer searching, molecular property calculations, pro...

GitHub

clinical-decision-support

hxk622

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommenda...

GitHub

geo-database

hxk622

Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.

GitHub

reactome-database

hxk622

Query Reactome REST API for pathway analysis, enrichment, gene-pathway mapping, disease pathways, molecular interactions, expression analysis, for systems biology studies.

GitHub

alphafold-database

hxk622

Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.

GitHub

chromatin-state-inference

BIsnake2001

This skill should be used when users need to infer chromatin states from histone modification ChIP-seq data using chromHMM. It provides workflows for chromatin state segmentation, model training, state annotati...

GitHub

functional-enrichment

BIsnake2001

Perform GO and KEGG functional enrichment using HOMER from genomic regions (BED/narrowPeak/broadPeak) or gene lists, and produce R-based barplot/dotplot visualizations. Use this skill when you want to perform G...

GitHub

motif-scanning

BIsnake2001

This skill identifies the locations of known transcription factor (TF) binding motifs within genomic regions such as ChIP-seq or ATAC-seq peaks. It utilizes HOMER to search for specific sequence motifs defined...

GitHub

local-methylation-profile

BIsnake2001

This skill analyzes the local DNA methylation profiles around target genomic regions provide by user. Use this skill when you want to vasulize the average methylation profile around target regions (e.g. TSS, CT...

GitHub

hic-normalization

BIsnake2001

Automatically detect and normalize Hi-C data. Only .cool or .mcool file is supported. All .mcool files are then checked for existing normalization (supports bins/weight only) and balanced if none of the normali...

GitHub

genomic-feature-annotation

BIsnake2001

This skill is used to perform genomic feature annotation and visualization for any file containing genomic region information using Homer (Hypergeometric Optimization of Motif EnRichment). It annotates regions...

GitHub

bam-filtration

BIsnake2001

Performs data cleaning and removal operations. This skill takes a raw BAM and creates a new, "clean" BAM file by actively removing artifacts: mitochondrial reads, blacklisted regions, PCR duplicates, and unmapp...

GitHub

loop-annotation

BIsnake2001

This skill annotates chromatin loops, including enhancer/promoter assignments, CTCF-peak overlap. It automatically constructs enhancer and promoter sets when missing and outputs standardized loop categories.

GitHub

alignment-level-qc

BIsnake2001

Calculates technical mapping statistics for any aligned BAM file (ChIP or ATAC). It assesses the performance of the aligner itself by generating metrics on read depth, mapping quality, error rates, and read gro...

GitHub

nested-tad-detection

BIsnake2001

This skill detects hierarchical (nested) TAD structures from Hi-C contact maps (in .cool or mcool format) using OnTAD, starting from multi-resolution .mcool files. It extracts a user-specified chromosome and re...

Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.

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