bioinformatics
2
ihara-zeta
Ihara zeta function for graphs: non-backtracking walks, prime cycles, and spectral analysis via det(I - uB).
plurigrid
research
sorting
stars
current ordering strategy
query
all entries
refine the visible subset
bioinformatics
2
gay-fokker-planck-staging
Two Fokker-Plancks per staging gate, conditioned on (rama OR goblins)
plurigrid
research
bioinformatics
2
mbius-color-duality
Möbius inversion for Gay.jl color duality - closes sparsification spine gap
plurigrid
research
bioinformatics
2
covariant-fibrations
Riehl-Shulman covariant fibrations for dependent types over directed
plurigrid
research
bioinformatics
2
yb-translator
Translate programming concepts to biological parallels using real ontology terms from EBI OLS.
plurigrid
research
bioinformatics
2
harmonic-centrality-transport
Harmonic centrality gadgets with GF(3) conservation for topological transport of ablative case structure via abelian extensions of ℚ
plurigrid
research
bioinformatics
2
sheaf-laplacian-coordination
Sheaf neural network coordination via graph Laplacians for distributed
plurigrid
research
bioinformatics
2
slime-strategy
Use when user wants to set up slime mold exploration strategy with parallel autonomy branches for genetic algorithm approach to problem-solving
tilmon-engineering
research
bioinformatics
2
spi-parallel-verify
Verify Strong Parallelism Invariance (SPI) and GF(3) conservation for 3-way color streams with arbitrary precision.
plurigrid
research
bioinformatics
1
networkx
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
hxk622
research
bioinformatics
1
etetoolkit
Phylogenetic tree toolkit (ETE). Tree manipulation (Newick/NHX), evolutionary event detection, orthology/paralogy, NCBI taxonomy, visualization (PDF/SVG), for phylogenomics.
hxk622
research
bioinformatics
1
asymptotic-theory
M-estimation, influence functions, and semiparametric efficiency theory for causal inference
Data-Wise
research
bioinformatics
1
neuropixels-analysis
Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL curation, AI-assisted visual analysis, for Neuropixels 1.0/2.0 extracellular electrophysiology. Use when working with neural recordings, spike sorting, extracellular electrophysiology, or when the user mentions Neuropixels, SpikeGLX, Open Ephys, Kilosort, quality metrics, or unit curation.
hxk622
research
bioinformatics
1
mechinterp-investigator
Orchestrate a systematic research program to investigate and meaningfully label SAE features
cesaregarza
research
bioinformatics
1
lamindb
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
hxk622
research
bioinformatics
1
scvi-tools
Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects, multimodal data. For standard analysis pipelines use scanpy.
hxk622
research
bioinformatics
1
arboreto
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.
hxk622
research
bioinformatics
1
cross-disciplinary-ideation
Field connection mapping and systematic ideation for method transfer
Data-Wise
research
bioinformatics
1
pathml
Full-featured computational pathology toolkit. Use for advanced WSI analysis including multiplexed immunofluorescence (CODEX, Vectra), nucleus segmentation, tissue graph construction, and ML model training on pathology data. Supports 160+ slide formats. For simple tile extraction from H&E slides, histolab may be simpler.
hxk622
research
bioinformatics
1
methods-paper-writer
JASA/Biometrika manuscript structure with VanderWeele notation standards
Data-Wise
research