Use when wiring LLM APIs to bioinformatics analysis result tables in this repository, especially when users ask to interpret DEG, enrichment, ssGSEA, pathway-map, or…
Access a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required.
Use when you have a collection of molecular fingerprint vectors (such as biosynfoni count fingerprints) and need to measure structural similarity between all pairs of molecules.
Use when the user asks about TBtools, TBtools-II, TBtools RPC API, TBtools CLI, or bioinformatics operations available through TBtools such as sequence manipulation, BLAST,…
生物作业生成 Skill是面向班级作业的产品级 Hermes Skill，年级、册别、单元、知识点和难度通过参数传入。 Workflow: teacher_biology_homework_generation.run.
生物单元复习 Skill是面向单元复习的产品级 Hermes Skill，年级、册别、单元、知识点和难度通过参数传入。 Workflow: teacher_biology_unit_review.run.
Use when when you have validated SMILES strings or RDKit molecule objects representing chemical structures and need to feed them into a pre-trained deep learning model (such as…
Use when targeting The EMBO Journal (EMBO J) or deciding whether a mechanistic molecular biology manuscript fits this venue.
Use when targeting The Plant Cell or deciding whether a plant biology manuscript fits this venue. Encodes the journal's fit, framing, method-and-evidence bar, house style,…
Use when targeting The Plant Journal or deciding whether a plant-science manuscript fits this venue. Encodes the journal's fit, the mechanistic gene-to-function and…
Use when when you have peak-abundance .csv files with assigned molecular formulas (elemental composition: C, H, O, N, P, S) from FT-ICR MS or high-resolution MS and need to…
Use when you have downloaded or cloned a fragmentation library repository (such as LipidMatch) and need to verify that it contains the expected breadth of coverage across both…
Exhaustive problem space exploration using the MIT Synthetic Neurobiology "tiling tree" method. Partitions a problem into MECE (Mutually Exclusive, Collectively Exhaustive)…
Use when converting medical text between academic and patient-friendly tones, translating medical jargon for patients, adapting research papers for public audiences, or rewriting…
Discover novel small molecule binders for protein targets using structure-based and ligand-based approaches.
Provide comprehensive clinical interpretation of somatic mutations in cancer. Given a gene symbol + variant (e.g., EGFR L858R, BRAF V600E) and optional cancer type, performs…
AI-driven patient-to-trial matching for precision medicine and oncology. Given a patient profile (disease, molecular alterations, stage, prior treatments), discovers and ranks…
Generates comprehensive drug research reports with compound disambiguation, evidence grading, and mandatory completeness sections.
Production-ready genomics and epigenomics data processing for BixBench questions. Handles methylation array analysis (CpG filtering, differential methylation, age-related CpG…
Comprehensive immune repertoire analysis for T-cell and B-cell receptor sequencing data. Analyze TCR/BCR repertoires to assess clonality, diversity, V(D)J gene usage, CDR3…
Neuroscience research workflows: neuroanatomy, neural circuits, neurotransmitter biology, neurological/psychiatric disease genetics, neural-protein function.
Production-ready phylogenetics and sequence analysis skill for alignment processing, tree analysis, and evolutionary metrics.
Comprehensive patient stratification for precision medicine by integrating genomic, clinical, and therapeutic data.
Provide actionable treatment recommendations for cancer patients based on molecular profile. Interprets tumor mutations, identifies FDA-approved therapies, finds resistance…
Retrieves protein structure data from RCSB PDB, PDBe, and AlphaFold with protein disambiguation, quality assessment, and comprehensive structural profiles.
Production-ready RNA-seq differential expression analysis using PyDESeq2. Performs DESeq2 normalization, dispersion estimation, Wald testing, LFC shrinkage, and result filtering.
Retrieves biological sequences (DNA, RNA, protein) from NCBI and ENA with gene disambiguation, accession type handling, and comprehensive sequence profiles.
Production-ready single-cell and expression matrix analysis using scanpy, anndata, and scipy. Performs scRNA-seq QC, normalization, PCA, UMAP, Leiden/Louvain clustering,…
Comprehensive systems biology and pathway analysis using multiple pathway databases (Reactome, KEGG, WikiPathways, Pathway Commons, BioModels).
Gather comprehensive biological target intelligence from 9 parallel research paths covering protein info, structure, interactions, pathways, expression, variants, drug…
Production-ready VCF processing, variant annotation, mutation analysis, and structural variant (SV/CNV) interpretation for bioinformatics questions.
Research any topic end to end and get back a fact-checked, branded HTML report plus an agent-readable markdown brief.
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep lear — from…
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep lear — from…
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep lear — from…
PyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modeling, or knowledge graph reaso — from…
PyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modeling, or knowledge graph reaso — from…
Graph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, G — from…
PyTorch-native Graph Neural Network framework for molecules and proteins. Suitable for building custom GNN architectures for drug discovery, protein modeling, or knowledge graph…
PyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modeling, or knowledge graph reaso — from…
Use when you have collected liquid chromatography (LC) spectra and retention time labels for your in-house molecular database, and you want to leverage a pretrained GNN-RT model…
Use when you have raw or processed arrival-time data from a TWIM-MS instrument and need to convert it to CCS values for comparison across experiments or biomolecular classes.
Use when you have TWIM-MS data (arrival time and m/z values) from a multi-omic sample and need to: (1) establish a CCS calibration curve from known standards, (2) assign…
Query UCSC Genome Browser REST API for DNA sequences, tracks, gene models, and conservation across 100+ assemblies.
Atomic-design guidance for Molecules — functional groups of atoms (SearchBar = input + button + icon; FormField = label + input + error) with a single cohesive purpose.
This pipeline performs genome-wide segmentation of CpG methylation profiles to identify Unmethylated Regions (UMRs), Low-Methylated Regions (LMRs), and Partially Methylat — from…
Use when when you have parallel mass spectra and molecular structure data (e.g., CANOPUS or MassSpecGym datasets) and aim to train a single encoder-decoder model (e.g., BART) that…
Use when when you have a ranked list of GCF-MF (genomic cluster family–molecular feature) link predictions from one or more scoring functions, a curated set of known validated…
Use when when you have scored GCF-MF (gene cluster family–molecular family) links using two or more complementary scoring approaches (e.g., standardised strain correlation and…
变异与区间文件处理 skill。用于 VCF/BCF、BED、GFF/GTF、interval_list、peak、DMR、loop、genomic ranges 的过滤、合并、交集、注释、坐标系转换和 genome build 一致性检查。
Search PubMed with veterinary-specific filters and MeSH terms to find relevant animal health research. Handles the sparse, multi-species nature of veterinary literature.
Generate R/Python code for volcano plots from DEG (Differentially Expressed Genes) analysis results. Triggered when user needs visualization of gene expression data, p-value vs…
Waddington's epigenetic landscape: cell fate as gradient flow on potential surfaces, connecting developmental biology to dynamical systems, Schrödinger bridges, and fractional…
Use when when you have a parsed mass spectrum (precursor m/z, ionization mode, collision energy, and fragment peak list as m/z–intensity pairs) and need to obtain molecular…
Build whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (U — from…
Use when when you have pre-processed MS/MS spectra and a pre-trained Word2Vec model, and need to compute fast, scalable similarity scores for library matching or molecular…
Use when when comparing large numbers of MS/MS spectra against spectral libraries or in molecular networking, particularly when molecules differ by multiple structural…
Use when when applying a pre-trained Word2Vec model to mass spectra at inference time (e.g., library matching or molecular networking), especially when the query spectra may…
Decompose goals into MEOWs (Molecular Expressions of Work) - trackable atomic units following Gas Town's bead-based work model.
Use when when you have a multi-step computational chemistry or molecular modeling pipeline (3+ sequential or parallel stages) that must process many molecules, each requiring…