Results for “sequences”

Read, write, and manipulate genomic datasets including SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences using a Pythonic interface to htslib.

Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines

Guidance for writing Remotion React markup with animation patterns, media handling, sequences, effects, and advanced features like 3D, audio visualization, and parameterized videos.

Apply named refactoring transformations to improve code structure without changing behavior, guided by code smells and safe transformation sequences.

Generate aerial drone-perspective footage with sweeping bird's-eye views, orbit shots, and flyover sequences for landscapes, architecture, and events.

Submit protein sequences to the Adaptyv Bio Foundry for experimental characterization (binding, thermostability, expression, fluorescence) and retrieve results using the REST API or Python SDK.

Use when you need to remove adapter sequences from high-throughput sequencing reads, trim low-quality bases, or filter reads by length. Supports single-end and paired-end FASTQ/FASTA input with error-tolerant adapter matching.

Enforce consistent frontend UX patterns for Ethereum dApps: onchain buttons, four-state connect flows, token approval sequences, address display, USD values, and RPC configuration.

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

Predict continuous values from temporal sequences using aeon's time series regressors, covering convolutional, deep learning, distance-based, feature-based, hybrid, interval-based, and shapelet-based approaches.

Explains MariaDB-specific features and behaviors that differ from MySQL, including system-versioned tables, RETURNING, sequences, and version-specific defaults, to help optimize and migrate MariaDB applications.

Explains MariaDB-specific TRUNCATE TABLE semantics: DROP privilege, implicit commit, AUTO_INCREMENT reset, trigger and FK behavior, and restrictions on system-versioned tables and sequences.

Build complex, interactive animations in React/Next.js including drag-and-drop, gestures, text animations, SVG path drawing, custom hooks, and imperative sequences.

Submit protein sequences to the Adaptyv Bio Foundry for experimental characterization (binding, thermostability, expression, fluorescence) and retrieve results via API or Python SDK.

Build quiz and assessment funnels that generate qualified leads through interactive scorecards, covering concept hooks, question design, dynamic results, and automated follow-up sequences.

Generates a complete marketing pipeline for apps, dev tools, and SaaS products, including positioning, listing assets, launch plans, and growth strategies, adapting to product type.

Predicts chromatin state across 919 tracks (histone marks, DNase, TF binding) for DNA sequences via the hosted Genomic Intelligence API, producing a report and JSON results.

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.

Submits and tracks protein-testing experiments on the Adaptyv Bio Foundry cloud lab (wet-lab validation), and optimizes protein sequences before submission with computational tools (NetSolP, SoluProt, SolubleMPNN, ESM). Use when designing proteins that need wet-lab validation - binding/affinity screening, expression testing, thermostability, or fluorescence assays - or when submitting experiments to the Foundry API, browsing the target catalog, tracking experiment status, retrieving results, or pre-screening sequences for solubility/expression. Triggers on "Adaptyv", "Foundry API", "cloud lab", "biolayer interferometry / BLI", "wet-lab validation". Part of the AlterLab Academic Skills suite.

Drafts and sequences internal change-management communications (re-orgs, layoffs, policy changes) using ADKAR and Kotter models, producing announcement text, FAQ, manager talking points, and a touchpoint calendar.

Injects up to 1 million tokens of external context into AI agent memory, auto-summarizes conversations with tone and intent preservation, and compresses multi-turn history into dense token sequences.

Analyze PCAP files by reconstructing TCP/UDP sessions, decoding application-layer protocols, and correlating packet sequences with host or malware behavior for CTF challenges.

Design high-converting marketing emails with layout patterns, subject line formulas, and deliverability rules. Covers welcome sequences, promotional emails, transactional templates, and mobile optimization.

Designs and maintains versioned reusable task sequences in Financial Services Cloud using Action Plan templates for client onboarding, account opening, annual review preparation, and compliance tasks.

Analyze content sequences from page structure to determine whether each should be default content or a specific block, and validate block selection for AEM Edge Delivery Services imports.

Analyze and engineer protein glycosylation by scanning sequences for N-glycosylation sequons, predicting O-glycosylation hotspots, and accessing curated glycoengineering tools for therapeutic antibody optimization and vaccine design.

Draft a professional, audience-aware email or reply with calibrated tone and a clear call to action. Use when the user needs one message, response, follow-up, support note, or meeting request; use sales-email-sequences for a coordinated multi-touch outbound campaign.

Detect splice donor and acceptor sites in DNA sequences using the Genomic Intelligence G0 BigBird transformer, via the hosted /v1/tasks/splice/predict API. Returns per-position site probabilities and called sites.

Foundational Clojure patterns covering functional programming, REPL-driven development, immutable data structures, and idiomatic code. Use when writing Clojure code, working with sequences and lazy evaluation, understanding macros, or needing guidance on functional programming patterns. This is the entry point for Clojure development.

State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.

State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.

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.

Reimplements DnaSP 6 for population genetics analysis of aligned DNA sequences, including nucleotide diversity, haplotype statistics, neutrality tests, linkage disequilibrium, recombination, mismatch distribution, InDel polymorphism, between-population divergence, outgroup-based tests, HKA test, McDonald-Kreitman.

Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.

Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.

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.