Results for “dna-sequence”

Predicts gene and transcript structure from a DNA sequence using the hosted Genomic Intelligence API, producing a report and JSON output.

Use when searching DNA or RNA queries against nucleotide sequence databases with HMMER's nucleotide homology search engine.

Analyzes raw genomic data (FASTQ/VCF) to generate non-medical wellness, longevity, and pharmacogenomic optimization protocols while keeping DNA processing local and private.

Orchestrates a complete bulk RNA-seq differential-expression study from raw FASTQ reads through QC, alignment, quantification, differential expression, pathway enrichment, and publication figures.

Performs differential expression analysis on bulk RNA-seq or pseudo-bulk count matrices with QC, PCA, and contrast testing.

Analyze biological sequences, alignments, phylogenetic trees, and diversity metrics (alpha/beta, UniFrac) with ordination (PCoA) and PERMANOVA for microbiome and community ecology data.

Query the 1000 Genomes Project dataset at the individual participant level to find variants, carriers, and relatedness information.

When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-cro.

Hunt for DNS-based persistence mechanisms including DNS hijacking, dangling CNAME records, wildcard DNS abuse, and unauthorized zone modifications using passive DNS databases, SecurityTrails API, and DNS audit log analysis.

Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.

Translates raw genomic data into personalized health, longevity, and pharmacogenomic protocols for AI agents.

Provides Python bindings to interact with the DNAnexus platform, enabling file uploads, job management, and API calls.

Detect promoter regions in DNA sequences by calling the Genomic Intelligence G0 transformer (GENA-LM BERT Large) hosted API. Returns per-window promoter probabilities and called regions as a report and JSON, from a single FASTA input.

Access the European Nucleotide Archive (ENA) via its API and FTP to retrieve DNA/RNA sequences, raw sequencing reads (FASTQ), and genome assemblies by accession, with support for multiple formats. Use when downloading reads or sequences for a study, run, or sample accession, or when sourcing nucleotide data for genomics and bioinformatics pipelines. Part of the AlterLab Academic Skills suite.

Use when profiling nucleotide content (AT/GC percentages, base counts) of genomic intervals against a FASTA reference.

Query 20+ bioinformatics databases from the command line or Python for gene information, sequences, protein structures, enrichment analysis, and more.

Runs and manages DNAnexus jobs and workflows, including monitoring, parallel execution, and error handling.

Annotates single-cell RNA-seq data by scoring marker genes, transferring labels with CellTypist, or reasoning over marker lists with an LLM.

Runs NCBI BLAST+ 2.17.0 sequence searches from the command line: makeblastdb (with -parse_seqids), blastn/blastp/blastx/tblastn with tabular -outfmt 6/7 for parsing, correct -task choice (megablast vs blastn vs blastn-short), -taxids/-negative_taxids taxonomic scoping, and -mt_mode multithreading; plus a DIAMOND blastp --ultra-sensitive path for large protein searches. Warns that -max_target_seqs is a heuristic keep-count, not a top-N best-hits filter. Use when the user wants command-line BLAST, makeblastdb, a local BLAST database, blastn/blastp/blastx/tblastn searches, or DIAMOND protein search. For the Bio.Blast web NCBIWWW API prefer alterlab-biopython; for quick one-liner database lookups prefer alterlab-gget. Part of the AlterLab Academic Skills suite.

Build and deploy apps/applets on the DNAnexus cloud genomics platform, manage data objects, run workflows, and use the dxpy Python SDK for genomics pipeline development and execution.

When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email...

Análise de RNA-seq de célula única. Carregue dados .h5ad/10X, QC, normalização, PCA/UMAP/t-SNE, clustering Leiden, genes marcadores, anotação de tipo celular, trajetória, para análise de scRNA-seq.

Query NCBI Gene via the E-utilities and Datasets APIs, searching by gene symbol or Gene ID and retrieving gene information (RefSeqs, GO terms, genomic locations, associated phenotypes) including batch lookups. Use when resolving gene symbols to IDs, annotating gene lists, or pulling functional and positional gene metadata for downstream analysis. Part of the AlterLab Academic Skills suite.

When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-cro.

Use when aligning short reads to a reference genome or indexed sequence database. Suitable for mapping FASTQ/FASTA reads in paired-end or single-end mode to produce SAM output.

Analyze any text to extract a cognitive fingerprint across 12 dimensions, revealing reasoning patterns, decision styles, and thinking signatures.

Detects DNS tunneling by computing Shannon entropy of DNS query names, analyzing query length distributions, inspecting TXT record payloads, and identifying high subdomain cardinality using scapy for packet capture analysis.

Cross-runtime 2-stage pipeline for Claude Code, Codex/OMX, and Gemini/Antigravity/OMA: trace causal hypotheses, inject evidence into deep-interview style requirements crystallization, then hand off to the right runtime planner/executor.

Perform differential gene expression analysis for bulk RNA-seq data using PyDESeq2, supporting formulaic designs, Wald tests, FDR correction, LFC shrinkage, and result visualization.

Process and analyze high-throughput sequencing data with deepTools for quality control, normalization, comparison, and publication-quality visualizations of ChIP-seq, RNA-seq, and ATAC-seq experiments.