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cccskills

「biology」の検索結果

125 件 ・ 関連度順

概要と使いどころ

Expert-level computational biology covering molecular dynamics simulation, protein structure prediction, systems biology, network analysis, and machine learning in biology.

日本語の概要は準備中です。原文の説明を表示しています。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Expert-level microbiology covering bacterial and viral biology, microbial physiology, pathogenesis, antimicrobial resistance, microbiome science, and industrial microbiology.

日本語の概要は準備中です。原文の説明を表示しています。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Use when interpreting biological research findings, evaluating life science evidence, analyzing molecular or cellular mechanisms, comparing competing biological hypotheses, designing or critiquing experiments in biology, genetics, genomics, cell biology, immunology, neuroscience, ecology, or any life science domain. Triggers on questions about gene function, pathways, phenotypes, GWAS hits, single-cell data, animal models, clinical translation, evolutionary arguments, or any biology/life science reasoning task.

日本語の概要は準備中です。原文の説明を表示しています。

Agents365-ai/365-skills842026年10月3日 更新

Comprehensive biology expert from molecular biology to ecology, covering cell biology, genetics, evolution, and physiology

日本語の概要は準備中です。原文の説明を表示しています。

sandraschi/advanced-memory-mcp192026年10月10日 更新

Expert-level cell biology knowledge. Use when working with cell structure, organelles, cell signaling, cell cycle, cell division, cytoskeleton, membrane biology, vesicular trafficking, apoptosis, or cell biology techniques. Also use when the user mentions 'organelle', 'mitochondria', 'endoplasmic reticulum', 'Golgi', 'cytoskeleton', 'cell cycle', 'mitosis', 'meiosis', 'apoptosis', 'signal transduction', 'membrane potential', 'endocytosis', or 'cell migration'.

日本語の概要は準備中です。原文の説明を表示しています。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Expert-level marine biology covering ocean ecosystems, marine organisms, coral reef ecology, deep sea biology, fisheries science, ocean chemistry, and marine conservation.

日本語の概要は準備中です。原文の説明を表示しています。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Use when targeting Global Change Biology or deciding whether a biology/ecology manuscript fits this venue. Encodes the journal's fit, the global-change-driver framing and biological-evidence bar, scale and mechanism expectations, house style, official-submission re-check, and desk-reject heuristics.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2422026年9月27日 更新

Use when targeting Annual Review of Plant Biology or deciding whether a plant-biology review proposal fits this invited-review venue. Encodes the journal's fit, the authoritative-synthesis and invited-article bar, evidence and balance expectations, house style, official-submission re-check, and desk-reject heuristics.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2422026年9月27日 更新

Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or Chronos. Covers screen-specific batch sources (passage cohort, library lot, infection day, sequencing run, Cas9 lot, FBS lot), PCA + variance-decomposition diagnostic to decide if correction is needed, when correction harms biology by over-correcting condition into batch, limma removeBatchEffect for visualization-only correction, and relationship to multi-condition design matrices. Use when combining screens for joint analysis, when passage cohort confounds biology, when DepMap-style panels need Chronos with batch covariates, when picking ComBat vs RUV, or when correction harms biology and should be replaced with explicit covariate modeling.

日本語の概要は準備中です。原文の説明を表示しています。

GPTomics/bioSkills1,2192026年8月15日 更新

Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or Chronos. Covers screen-specific batch sources (passage cohort, library lot, infection day, sequencing run, Cas9 lot, FBS lot), PCA + variance-decomposition diagnostic to decide if correction is needed, when correction harms biology by over-correcting condition into batch, limma removeBatchEffect for visualization-only correction, and relationship to multi-condition design matrices. Use when combining screens for joint analysis, when passage cohort confounds biology, when DepMap-style panels need Chronos with batch covariates, when picking ComBat vs RUV, or when correction harms biology and should be replaced with explicit covariate modeling.

日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2002026年7月2日 更新

Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or Chronos. Covers screen-specific batch sources (passage cohort, library lot, infection day, sequencing run, Cas9 lot, FBS lot), PCA + variance-decomposition diagnostic to decide if correction is needed, when correction harms biology by over-correcting condition into batch, limma removeBatchEffect for visualization-only correction, and relationship to multi-condition design matrices. Use when combining screens for joint analysis, when passage cohort confounds biology, when DepMap-style panels need Chronos with batch covariates, when picking ComBat vs RUV, or when correction harms biology and should be replaced with explicit covariate modeling.

日本語の概要は準備中です。原文の説明を表示しています。

lilinji/GeneTind-Life-Skills142026年8月21日 更新

Expert-level developmental biology covering embryogenesis, cell fate determination, morphogen gradients, organogenesis, stem cells, and regenerative medicine.

日本語の概要は準備中です。原文の説明を表示しています。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or Chronos. Covers screen-specific batch sources (passage cohort, library lot, infection day, sequencing run, Cas9 lot, FBS lot), PCA + variance-decomposition diagnostic to decide if correction is needed, when correction harms biology by over-correcting condition into batch, limma removeBatchEffect for visualization-only correction, and relationship to multi-condition design matrices. Use when combining screens for joint analysis, when passage cohort confounds biology, when DepMap-style panels need Chronos with batch covariates, when picking ComBat vs RUV, or when correction harms biology and should be replaced with explicit covariate modeling.

日本語の概要は準備中です。原文の説明を表示しています。

peacezha/HPClaw32026年10月11日 更新

Use when targeting Soil Biology & Biochemistry or deciding whether a soil-science manuscript fits this venue. Encodes the journal's fit, the soil-process-mechanism bar, evidence and data-reporting expectations, house style, official-submission re-check, and desk-reject heuristics.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2422026年9月27日 更新

Fit SimBiology model parameters to data — fitproblem, population NLME, virtual patients, and NCA. Use when asked to fit, estimate, calibrate, or compute PK metrics.

日本語の概要は準備中です。原文の説明を表示しています。

matlab/matlab-agentic-toolkit1,1512026年10月9日 更新

Build, modify, and diagram SimBiology models — API reference, helper functions, and layout patterns. Use when constructing or editing models programmatically or visually.

日本語の概要は準備中です。原文の説明を表示しています。

matlab/matlab-agentic-toolkit1,1512026年10月9日 更新

Simulate SimBiology models — ODE, stochastic (SSA), scenarios, and sensitivity analysis. Use when asked to run, simulate, predict, explore what-if, or identify influential parameters.

日本語の概要は準備中です。原文の説明を表示しています。

matlab/matlab-agentic-toolkit1,1512026年10月9日 更新

Molecular biology toolkit: sequence manipulation, FASTA/GenBank/PDB I/O, NCBI Entrez, BLAST automation, pairwise/MSA alignment, Bio.PDB, phylogenetic trees. Use for batch processing, custom pipelines, format conversion, PubMed/GenBank queries. For quick gene lookups use gget; for multi-service REST APIs use bioservices.

日本語の概要は準備中です。原文の説明を表示しています。

jaechang-hits/SciAgent-Skills3762026年9月29日 更新

Use when evaluating biology grant ideas in the Chinese funding context (NSFC, MOST, etc.) — diagnosing project legitimacy, mechanism-centered scientific questions, reviewer-aware logic, innovation discipline, feasibility, and scope control across funding levels (youth, general, key).

日本語の概要は準備中です。原文の説明を表示しています。

Agents365-ai/365-skills842026年10月3日 更新

Use when a task needs the judgment of a Biology Professor at a research university — writing or defending an NIH/NSF grant budget, deciding authorship order on a paper, navigating an IACUC or biosafety protocol, mentoring a PhD student through a stalled project, or converting a course when active-learning data doesn't match student pushback.

日本語の概要は準備中です。原文の説明を表示しています。

wonsukchoi/domain-experts202026年10月5日 更新

Expert-level planetary science covering solar system formation, planetary interiors, atmospheres, surface processes, astrobiology, and planetary exploration missions.

日本語の概要は準備中です。原文の説明を表示しています。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Expert-level molecular biology knowledge. Use when working with DNA replication, transcription, translation, gene regulation, cloning, PCR, sequencing, CRISPR, epigenetics, or molecular techniques. Also use when the user mentions 'DNA replication', 'transcription', 'translation', 'gene expression', 'PCR', 'cloning', 'restriction enzyme', 'gel electrophoresis', 'Western blot', 'CRISPR', 'epigenetics', 'promoter', 'enhancer', or 'RNA splicing'.

日本語の概要は準備中です。原文の説明を表示しています。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Expert-level biochemistry from a biology perspective covering metabolic pathways, enzyme kinetics, bioenergetics, signal transduction, and the biochemical basis of cellular processes.

日本語の概要は準備中です。原文の説明を表示しています。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Expert-level bioinformatics covering sequence analysis, structural bioinformatics, database searching, phylogenetic analysis, NGS data processing, single-cell analysis, and machine learning in biology.

日本語の概要は準備中です。原文の説明を表示しています。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新