Results for “chembl”

Primary Python tool for 40+ bioinformatics services. Preferred for multi-database workflows: UniProt, KEGG, ChEMBL, PubChem, Reactome, QuickGO. Unified API for queries, ID mapping, pathway analysis. For direct REST control, use individual database skills (uniprot-database, kegg-database).

Automate Lemlist multichannel outreach: manage campaigns, enroll leads, add personalization variables, export campaign data, and handle unsubscribes via the Composio MCP integration.

Add the /bl switch to MSBuild-based commands to generate binary logs for build diagnostics and performance analysis.

Train unsupervised machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.

Local search/indexing CLI (BM25 + vectors + rerank) with MCP mode.

Filters and prioritizes compound libraries in drug discovery using drug-likeness rules, structural alerts, complexity metrics, and a query language.

Query Belgian railway (NMBS/SNCB) schedules via the irail CLI.

Trains machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.

This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.

Adopts the voice and comedic methodology of filmmaker Mel Brooks to craft parody, satire, and humor in responses.

Create and manage Kubernetes workloads with declarative YAML manifests, covering deployments, networking, security, storage, Helm charts, and troubleshooting.

Apply medicinal chemistry filters for compound triage: drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and a custom query language for library filtering.

Queries Belgian railway (NMBS/SNCB) schedules via the iRail CLI, including departures, connections, train compositions, and service disruptions.

编写、修改、审查 .cnb.yml 流水线配置，诊断构建失败原因并优化性能。

Machine learning on genomic interval data (BED files) with the geniml Python package — region embeddings (Region2Vec), joint region+metadata embeddings (BEDspace/StarSpace), single-cell ATAC-seq embeddings (scEmbed), consensus peak sets / universes (build-universe), tokenization, BEDshift randomization, and BBClient/BEDbase caching. Use when training or using region/cell embeddings, clustering scATAC-seq, building a tokenization universe from BED collections, or any ML/feature-learning task over genomic regions. NOT for plain interval arithmetic (overlap/intersect/merge counts) — that is gtars, not geniml. Part of the AlterLab Academic Skills suite.

Indexes local files and searches them with BM25, vector, and hybrid queries, plus MCP mode.

Runs Semgrep static analysis with custom YAML rules, supporting taint tracking, metavariable comparisons, and pattern-not-inside exclusions for precise vulnerability detection.

Access 100+ LLMs including Claude, Gemini, Kimi, and GLM via the inference.sh CLI with automatic fallback and cost optimization.

Use Geniml for audited local genomic-interval workflows: validate BED and universe contracts, plan Region2Vec or scEmbed runs, inspect model/tokenizer compatibility, and assess consensus universes.

Convert chemical structures (SMILES or RDKit molecules) into numerical representations for machine learning using 100+ featurizers, including ECFP, MACCS, descriptors, and pretrained models like ChemBERTa.

Builds, transpiles, and runs quantum circuits with Qiskit, IBM's quantum computing framework, including Qiskit Runtime primitives (Sampler/Estimator), circuit transpilation, and error mitigation on IBM Quantum hardware. Use when targeting IBM Quantum backends, transpiling circuits, running Runtime sessions or batches, or applying resilience/error mitigation. For Google Quantum AI hardware and NISQ circuits prefer alterlab-cirq; for gradient-trained quantum ML and hybrid quantum-classical models prefer alterlab-pennylane; for open-system Lindblad/master-equation dynamics prefer alterlab-qutip. Part of the AlterLab Academic Skills suite.

Coordinate agents via the AMQ CLI for file-based inter-agent messaging. Use this skill whenever you need to send messages to another agent (codex, claude, or any named handle), check your inbox, drain queued messages, set up co-op mode between agents, join a swarm team, route messages across projects, or diagnose delivery issues. Also use it when you receive a message and need to know how to reply, inspect receipts, or handle priority. Covers any multi-agent coordination task where agents need to talk to each other — review requests, questions, status updates, decision threads, wake notifications, and orchestrator integration (Symphony, Kanban). For collaborative spec/design workflows specifically, prefer the /amq-spec skill which provides structured phase-by-phase guidance. Not intended for distributed systems design (RabbitMQ, Kafka), CI/CD pipelines, or single-agent tasks with no partner.

沈墨（悬疑剧虚构）认知与表达框架（压缩蒸馏）：创伤反杀叙事、时代灰雾、钢琴意象 触发：漫长的季节 等。虚构；禁止犯罪模仿

IBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware...

Read-only EVM client: wallets, tokens, gas across 8 chains.

This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.

NOXA Fun/DEX collab for Cheshire Terminal — launch feed, DEX registry, QuoterV2 quotes, EVM RPC. One-shot npm package @x402solana/cheshire-noxa.

Translate and dub audio/video into 29 languages while preserving speaker voice using the inference.sh CLI.

Audit, write, or update CHANGELOG.md following Keep a Changelog 1.1.0. Use when creating a CHANGELOG, or reviewing commits to ensure Unreleased reflects user-visible changes. Defers to auto-managed setups (changesets, release-please, git-cliff, semantic-release, towncrier) and applies semver 2.0.0 — or Haskell PVP for Haskell projects.

Use to build an account's cumulative support record ahead of a renewal or QBR, so the review reflects the whole relationship rather than the most recent ticket. Trigger for "prepare for this renewal", "what has this account's support experience been", "which accounts are at risk before renewal", QBR preparation, account health review, or an account that renewed badly with no warning.

IBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip.

Build, optimize, and execute quantum circuits on IBM Quantum hardware or local simulators using Qiskit, including transpilation, primitives, and algorithm libraries.

Embody Jack Welch's direct, competitive leadership voice and apply his management methodology, including differentiation, Work-Out sessions, and boundaryless organization principles.

Detects available memory tools and maps them to a structured memory system for cross-session recall, with file-based fallback.