“sequences”的搜索结果

Think through the consequences of consequences — not just what happens immediately, but what happens next, and next after that, across time. Load when a decision looks obviously good or obviously bad on initial read, when the user is optimising for a short-term outcome that might create a long-term problem, when unintended consequences are a concern, or when deep-thinking diagnoses a second-order frame. Triggers on "what are the downstream effects", "what happens after that", "unintended consequences", "think ahead on this", "long-term vs short-term", or "what comes after that". Based on Howard Marks second-level thinking and Farnam Street mental models. Most powerful for decisions with delayed consequences or systemic effects.

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Design automated email sequences for new subscribers, prospective buyers, product users, and inactive customers. Get a flow with entry triggers, timing, exit conditions, subject lines, full email copy, clear next steps, and a measurement plan.

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• Create a welcome series for new subscribers
• Plan educational emails for prospective buyers
• Write product onboarding email sequences

Process DNA, RNA, and protein sequences with Biopython, convert biological files, and retrieve NCBI records. Supports batch workflows for sequence comparison, searches for similar sequences, protein structure analysis, and evolutionary trees.

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• Convert GenBank files to FASTA
• Calculate sequence length and GC content in batches
• Retrieve sequences and publication records from NCBI

Design protein sequences using ProteinMPNN inverse folding. Use this skill when: (1) Designing sequences for RFdiffusion backbones, (2) Redesigning existing protein sequences, (3) Fixing specific residues while designing others, (4) Optimizing sequences for expression or stability, (5) Multi-state or negative design. For backbone generation, use rfdiffusion or bindcraft. For ligand-aware design, use ligandmpnn. For solubility optimization, use solublempnn.

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Use the gget command line or Python package to look up genes, retrieve sequences, compare similar sequences, and explore biological database results. Save outputs and query details to support reproducible first-pass bioinformatics research.

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• Finding gene identifiers and transcript information
• Retrieving nucleotide or amino-acid sequences
• Running quick BLAST or BLAT sequence searches

Build interactive animations in React or Next.js, including draggable elements, swipe gestures, animated text, SVG line drawing, and loading indicators. Guides API selection and multi-step animation sequences, with touch testing and cleanup practices.

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• Building draggable sheets and reorderable lists
• Adding word reveals and animated number counters
• Animating SVG lines and circular progress

Build coordinated animation sequences with GSAP, an animation library. Arrange movements in order or in parallel, set start times with labels, group sequences inside others, and control playback, pauses, seeking, and reverse motion.

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• Playing several animations in a defined order
• Overlapping movements at precise start times
• Grouping sequences and controlling their playback

Build coordinated animation sequences with GSAP timelines. Set when each movement starts, overlap effects, name key moments, combine smaller sequences, and control playback, including pause, reverse, restart, and jumps to a specific point.

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• Animating several elements in a planned order
• Overlapping effects at precise times
• Organizing animation sections with labels

Build evolutionary trees from related nucleotide or protein sequences using MAFFT with IQ-TREE or FastTree. Review branch support, a measure of evidence for each grouping, and produce tree summaries and optional visualizations.

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• Build gene trees from related nucleotide sequences
• Compare evolutionary relationships within protein families
• Review branch support and analysis logs

Plan protein characterization experiments with Adaptyv's cloud laboratory, estimate costs, submit sequences, track progress, and retrieve measured results. Supports binding, thermal stability, expression, fluorescence, and enzyme activity workflows through the API and Python SDK.

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• Plan binding screens for candidate protein sequences
• Estimate experiment costs before submission
• Track laboratory progress and retrieve results

Automate lab data tasks in Benchling using its Python SDK and REST API. Import and export sequences, inspect sample inventory, and work with electronic lab notebooks and workflow tasks while checking schemas, permissions, and operation results.

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• Importing DNA sequences from FASTA files
• Auditing sample inventory at a storage location
• Exporting sequences for a specific schema to CSV

Use Biohub’s Python SDK to complete protein sequences with ESM3, extract numerical sequence representations with ESMC, and predict all-atom structures with ESMFold2. The skill guides local or hosted inference, input validation, and output checks.

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• Completing masked positions in protein sequences
• Extracting numerical features from protein sequences
• Predicting all-atom protein structures

Build and evaluate Mamba models for long sequences using state-space models, which summarize past inputs in an internal state. Covers setup, pretrained text generation, differences between Mamba-1 and Mamba-2, and speed comparisons with Transformers.

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• Generate text with pretrained Mamba models
• Compare Mamba-1 and Mamba-2 configurations
• Benchmark generation speed against Transformers

Integrate Flash Attention into transformer models to reduce processing time and GPU memory use for long sequences. Covers PyTorch integration, advanced attention options, and benchmarks that compare speed, memory use, and output accuracy.

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• Speeding up transformer training on long sequences
• Reducing GPU memory use during attention
• Adding Flash Attention to a PyTorch model

Document a technical decision in an architecture decision record, or ADR. Capture its context, alternatives, and consequences, assign a record number, and distinguish a proposed decision from an accepted one so dependent work reflects its actual status.

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• Recording the reasons behind a technical choice
• Documenting alternatives and consequences of a design decision
• Creating numbered records alongside existing architecture decisions

Build coordinated animation sequences with GSAP timelines. Set when each movement starts, overlap effects, name key moments, combine smaller sequences, and control playback, including pause, reverse, restart, and jumps to a specific point.

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• Animating several elements in a planned order
• Overlapping effects at precise times
• Organizing animation sections with labels

Implement Mamba, a model architecture that processes sequences through an internal state with computation scaling linearly with input length. Covers pretrained text generation, Mamba-1 and Mamba-2 configuration, speed comparisons with Transformers, and GPU memory troubleshooting.

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• Explore models for long sequences or streaming applications
• Generate text with pretrained Mamba models
• Compare Mamba-1 and Mamba-2 configurations

Optimize transformer attention, the calculation that relates tokens to one another, using Flash Attention. The skill guides PyTorch integration, GPU memory reduction, performance measurement, and output comparisons for training or inference with long sequences.

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• Reducing GPU memory use with long sequences
• Integrating Flash Attention into PyTorch models
• Comparing runtime and outputs before and after changes

Performs multiple sequence alignment of proteins with EBI Clustal Omega. Use when you need to align multiple sequences to assess similarity, domain conservation, or key residue conservation. Supports up to 4000 sequences and a maximum file size of 4 MB. Do not use to search for homologous proteins in a database (use MMseqs2, BLAST), align non-protein sequences (DNA, RNA), perform structural alignment (use Foldseek, PyMOL), or if you only have a single sequence.

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Retrieve protein and nucleotide sequences from NCBI databases using E-utilities. Supports direct accession lookup, CDS translation, gene+organism search, locus lookup, PubMed-linked sequences, patent protein extraction, and organism+length fallback search. Use when you need to fetch biological sequences by accession, gene name, locus tag, PubMed ID, or patent number.

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Filter and select sequences by criteria (length, ID, GC content, patterns) using Biopython. Use when subsetting sequences, removing unwanted records, or selecting by specific criteria.

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Generate consensus FASTA sequences by applying VCF variants to a reference using bcftools consensus. Use when creating sample-specific reference sequences or reconstructing haplotypes.

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Implement Apollo.io email sequences and outreach workflow. Use when building automated email campaigns, creating sequences, or managing outreach through Apollo. Trigger with phrases like "apollo email sequence", "apollo outreach", "apollo campaign", "apollo sequences", "apollo automated emails".

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Filter and select sequences by criteria (length, ID, GC content, patterns) using Biopython. Use when subsetting sequences, removing unwanted records, or selecting by specific criteria.

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