'sequences' 검색 결과

Provider-independent workflow for AI agents producing documentary-style montages, archive-driven timelines, interview-supported sequences, nonprofit or advocacy shorts, historical explainers, and hybrid generated/archive edits. Use for editorial thesis development, research/source logs, fact-checking, archive rights, synthetic reenactment disclosure, chronology, interview selects, lower thirds, generated b-roll direction, music restraint, captions, sensitive subjects, review escalation, delivery variants, and documentary QA.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Retrieve records from NCBI databases using Biopython Bio.Entrez (EFetch, ESummary). Use when downloading sequences, fetching GenBank/GenPept records, getting document summaries, parsing nested XML, navigating GI deprecation, choosing between rettype+retmode combinations, and parsing into Biopython SeqRecord/SwissProt objects. Covers nucleotide, protein, gene, pubmed, sra, gds, taxonomy, snp, clinvar.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyze codon usage, calculate CAI (Codon Adaptation Index), and examine synonymous codon bias using Biopython. Use when analyzing coding sequences for expression optimization or evolutionary analysis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Run remote BLAST searches against NCBI servers using Biopython Bio.Blast.NCBIWWW. Use when identifying unknown sequences, finding homologs, picking the correct BLAST program (blastn/blastp/blastx/tblastn/tblastx/psiblast/megablast/dc-megablast), interpreting Karlin-Altschul E-values, avoiding the max_target_seqs trap (Shah 2019), choosing composition-based statistics, or limiting searches by organism. Covers RID lifecycle, database choice (nt/nr/refseq_select/swissprot), word-size and CBS taxonomy.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyze restriction digest fragments using Biopython Bio.Restriction. Predict fragment sizes, get fragment sequences, simulate gel electrophoresis patterns, and perform double digests. Use when analyzing restriction digest fragment patterns.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Download large datasets from NCBI efficiently using EPost, history server, batching, rate limiting, and retry logic. Use when bulk-fetching tens of thousands of sequences, pulling all results of a large ESearch, designing reproducible pipelines, comparing E-utilities to NCBI Datasets v2 CLI, or implementing checksum-validated downloads. Encodes WebEnv TTL (~8h), EPost 200-ID limit, retmax caps, parallelization design, and integrity verification.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Reconstruct ancestral states at internal phylogenetic nodes for sequences (PAML codeml, IQ-TREE --ancestral, GRASP, FastML), discrete traits (corHMM hidden-rate Markov, ape::ace, phytools::make.simmap stochastic mapping, BayesTraits), and continuous traits (phytools::fastAnc, geiger Brownian/OU, RPANDA). Use when designing constructs for ancestral protein resurrection, tracing trait evolution along a tree, performing stochastic character mapping, testing models of trait evolution (BM vs OU vs EB), inferring ancestral genome content via Dollo or DTL reconciliation, or quantifying ancestral-state uncertainty for downstream comparative analyses.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Process multiple sequence files in batch using Biopython. Use when working with many files, merging/splitting sequences, or automating file operations across directories.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Convert raw Nanopore signal data (FAST5/POD5) to nucleotide sequences using Dorado basecaller. Covers model selection, GPU acceleration, modified base detection, and quality filtering. Use when processing raw Nanopore data before alignment. Note: Guppy is deprecated; use Dorado for all new analyses.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Query Ensembl for genomic data. Use when user asks about gene coordinates, genomic sequences, variants, gene structure, exons, transcripts, or species comparison. Triggers on "ensembl", "gene coordinates", "genomic location", "exon", "transcript", "variant location", "rsid", "rs number".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyze DNA/RNA/protein sequences. Use when the user provides a sequence and asks for analysis, translation, GC content, ORFs, motifs, restriction sites, or primer design. Triggers on "sequence", "translate", "GC content", "ORF", "primer", "restriction", "complement", "reverse complement".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Run BLAST sequence similarity searches. Use when the user asks to BLAST a sequence, find similar sequences, identify a gene/protein, or do homology search. Triggers on "blast", "sequence similarity", "homology", "identify sequence".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Remove sequencing adapters from FASTQ files using Cutadapt and Trimmomatic. Supports single-end and paired-end reads, Illumina TruSeq, Nextera, and custom adapter sequences. Use when FastQC shows adapter contamination or before alignment of short reads.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Query UniProt protein database. Use when user asks about protein sequences, functions, annotations, domains, or protein identifiers. Triggers on "uniprot", "protein function", "protein sequence", "gene product", "protein info".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Validate protein designs using AlphaFold2 structure prediction. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction with AlphaFold-Multimer. For faster single-chain prediction, use esm. For QC thresholds, use protein-qc.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Ligand-aware protein sequence design using LigandMPNN. Use this skill when: (1) Designing sequences around small molecules, (2) Enzyme active site design, (3) Ligand binding pocket optimization, (4) Metal coordination site design, (5) Cofactor binding proteins. For standard protein design, use proteinmpnn. For solubility optimization, use solublempnn.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

AlphaFold2 / AlphaFold-Multimer structure prediction for validation and confidence scoring. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction with AlphaFold-Multimer. For faster single-chain prediction, use esm2-sequence-scoring. For QC thresholds, use protein-design-qc.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Access UniProt for protein sequence and annotation retrieval. Use this skill when: (1) Looking up protein sequences by accession, (2) Finding functional annotations, (3) Getting domain boundaries, (4) Finding homologs and variants, (5) Cross-referencing to PDB structures. For structure retrieval, use pdb. For sequence design, use proteinmpnn.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Workflow for retrieving public omics datasets, sequences, annotations, and literature-linked biological resources.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build Tier 1/2/3 cold outreach sequences differentiated by personalization depth and research signal strength during PRD v0.9 Go-to-Market. Triggers on requests to plan cold outreach, founder-led sales, or when user asks "cold email sequence", "outbound campaign", "founder outreach", "LinkedIn outreach", "Tier 1 personalization", "predictable revenue", "sales cadence", "BDR sequence". Outputs GTM-OUT-* sequence entries and lead-list references.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Framework-driven copywriting for ads, landing pages, emails, sales pages, and CTAs. Includes AIDA, PAS, BAB, 4Ps, StoryBrand, QUEST, FAB, and more. Use when writing conversion-focused copy, ad creative, headlines, email sequences, sales pages, or when the user mentions copywriting frameworks, persuasive writing, or direct response copy.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Cold email and outreach sequence design with personalization, deliverability optimization, follow-up cadence, and compliance (CAN-SPAM/GDPR). Use when the user asks about cold email, outreach sequences, email prospecting, cold outreach, or email deliverability for outbound.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designs automated email sequences end to end: the trigger, branches and exit rules, the full copy of every message, and the sender setup that keeps them out of spam (SPF, DKIM, DMARC, one-click unsubscribe, consent). Covers onboarding and welcome series, lead nurture, abandoned cart, dunning, win-back and sunset flows. Use when someone asks for a "drip campaign", "welcome sequence", "onboarding emails", "nurture sequence", "win-back emails", "lifecycle emails", "email automation", or says "our emails land in spam" or "nobody clicks our onboarding emails". In-app onboarding belongs to onboarding-cro.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

You are an expert in Clay, the data enrichment and outbound sales platform that pulls from 75+ data providers to build rich prospect profiles. You help teams automate lead discovery, enrich contacts with firmographic and technographic data, score leads against ICP criteria, and trigger personalized outreach sequences — replacing manual research with automated, data-driven prospecting.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.