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Computed 78560

xuzhougeng/wisp-science

alphafold2

Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al. 2022, github.com/sokrypton/ColabFold; AlphaFold2 Jumper et al. 2021). Reach for this skill to fold a sequence or complex with the AF2/AF2-Multimer evoformer, to validate designed sequences by self-consistency pLDDT, ipTM, and RMSD, or to run a quick MSA-backed prediction using the public MMseqs2 server.

Computed 78560

xuzhougeng/wisp-science

local-env-setup

Use it for research tasks; the detail page covers purpose, installation, and practical steps.

Computed 78560

xuzhougeng/wisp-science

proteinmpnn

Inverse-fold a protein backbone (PDB structure) into amino-acid sequence with ProteinMPNN (Dauparas et al. 2022, github.com/dauparas/ProteinMPNN). Reach for this skill to run sequence design on RFdiffusion backbones, to redesign one chain of a PDB while holding interface residues fixed, or to generate a temperature-swept set of sequences for downstream folding.

Computed 77560

xuzhougeng/wisp-science

chai1

Structure prediction for protein, nucleic-acid, and small-molecule complexes with the Chai-1 foundation model (Chai Discovery 2024, github.com/chaidiscovery/chai-lab). Reach for this skill to predict an antibody-antigen or protein-ligand complex from a single FASTA, to re-fold designed binders as an AlphaFold-multimer alternative, or to drive co-folding from Python for batched campaigns on a GPU.

Computed 77560

xuzhougeng/wisp-science

evo2

Score, embed, and generate DNA sequences with Evo 2, a long-context genomic foundation model. Use this skill when: (1) Computing per-nucleotide or per-sequence likelihoods for variant effect scoring, (2) Embedding genomic windows for downstream classification, (3) Generating DNA conditioned on a prefix, (4) Scoring regulatory or coding regions across species.

Computed 77560

xuzhougeng/wisp-science

figure-composer

Compose or improve a publication-grade multi-panel scientific figure from a claim, concrete data paths, or an existing image. Use for figure outlining, parallel panel rendering, exact-grid composition, visual inspection, and adversarial figure review. Use figure-style for one standalone plot and paper-narrative for whole-paper figure ordering.

Computed 77560

xuzhougeng/wisp-science

indication-dossier

Generate a therapeutic indication dossier. Covers the patient population, epidemiology, disease biology, standard of care, regulatory precedent, and landmark clinical trials.

Computed 77560

xuzhougeng/wisp-science

using-model-endpoint

Invoke an already configured model endpoint from a supported Wisp execution context and capture the bounded inference as a Run. Use only when the endpoint URL and authentication are already available inside that context; this skill does not register or manage services.

Computed 76560

xuzhougeng/wisp-science

literature-review

Find, verify, and synthesize scientific literature — from "what's the seminal paper for X" through full multi-source reviews. Covers grounding claims in real retrieved sources, avoiding fabricated citations, handling retractions, and calibrating confidence to evidence strength.

Computed 75560

xuzhougeng/wisp-science

scgpt

Embed and annotate single-cell expression data with scGPT, a foundation model for single-cell biology. Use this skill when: (1) Producing cell embeddings from an AnnData for clustering/integration, (2) Zero-shot or fine-tuned cell-type annotation, (3) Gene-level representation for perturbation/GRN tasks. For probabilistic single-cell models (scVI etc.), use the scvi-tools library.

Computed 75560

xuzhougeng/wisp-science

scvi-tools

Probabilistic single-cell RNA-seq with scvi-tools — scVI for a batch-corrected latent space, scANVI for semi-supervised label transfer, and Bayesian differential expression. Reach for this skill to integrate scRNA-seq batches, embed cells for clustering, transfer annotations from a reference onto a query, or score differentially expressed genes per cluster. For spatial deconvolution / mapping use the cell2location, DestVI, or Tangram methods instead.

Computed 73560

xuzhougeng/wisp-science

agent-infini

Use the InfiniSynapse CLI (`agent_infini`) for multi-turn AI data-analysis tasks, database/RAG context, and task workspace files. Use when the user mentions InfiniSynapse, agent_infini, database or RAG analysis, or asks to delegate analysis through InfiniSynapse.

Computed 73560

xuzhougeng/wisp-science

solublempnn

Inverse-fold a backbone with SolubleMPNN — ProteinMPNN retrained on a soluble-PDB subset (Dauparas et al. 2022) — for sequences biased toward cytosolic expression and reduced aggregation. Reach for this skill when designs from vanilla ProteinMPNN are aggregating or going to inclusion bodies, when redesigning a membrane-adjacent fold for soluble expression, or when an E. coli expression screen is the next step.

Computed 72560

xuzhougeng/wisp-science

fair-esm2

Embed proteins with Meta AI's ESM-2 (`fair-esm` package). Use this skill when: (1) Extracting per-residue or per-sequence embeddings for downstream ML, (2) Masked-LM likelihood / mutation effect scoring, (3) Contact prediction from a sequence.

Computed 72560

xuzhougeng/wisp-science

paper-narrative

Judge and reshape the story told by a manuscript and its figure deck. Use when revising paper structure, testing whether Figure 1 is a hook, ordering figures, moving panels, identifying missing analyses, or defining the claim passed to figure-composer.

Computed 72560

xuzhougeng/wisp-science

pdf-explore

Use this skill when the user has attached a PDF, paper, report, or other document and the answer needs its content: summarize a section, compare sections, read specific pages, check the table of contents, or read a value off a figure. The `read` tool cannot parse PDF binary — python is the extraction path. Provides `pdf_pages` (pages as text or rendered PNGs, cached) and `pdf_outline` (embedded-bookmark TOC) in the persistent python kernel; load them once via the Kernel Sidecar exec line that `u

Computed 70560

xuzhougeng/wisp-science

borzoi

Predict genome-wide functional tracks (RNA-seq, CAGE, DNase, ChIP) from DNA sequence with Borzoi. Use this skill when: (1) Scoring the regulatory effect of a variant on expression/accessibility, (2) Generating predicted coverage tracks for a locus, (3) Prioritising non-coding variants by predicted track delta.

Computed 68560

xuzhougeng/wisp-science

bear-review

Review bear-review's use cases, installation, workflow, and original source instructions.

Computed 66560

xuzhougeng/wisp-science

bear-counter

Review bear-counter's use cases, installation, workflow, and original source instructions.

Computed 66560

xuzhougeng/wisp-science

bear-map

Use it for engineering tasks; the detail page covers purpose, installation, and practical steps.

Computed 66560

xuzhougeng/wisp-science

bear-onboard

Review bear-onboard's use cases, installation, workflow, and original source instructions.

Computed 66560

xuzhougeng/wisp-science

bear-propose

Review bear-propose's use cases, installation, workflow, and original source instructions.

Computed 66560

xuzhougeng/wisp-science

bear-scoop

Review bear-scoop's use cases, installation, workflow, and original source instructions.

Computed 66560

xuzhougeng/wisp-science

bear-support

Review bear-support's use cases, installation, workflow, and original source instructions.