Results for “multiple-sequence-alignment”

33 skills

Use when performing multiple sequence alignment of FASTA inputs, generating alignment ensembles, or calculating alignment confidence metrics.

Use when performing multiple sequence alignment on nucleotide or protein sequences, such as preparing alignments for phylogenetic analysis or comparative genomics.

Use when performing multiple sequence alignments on protein or nucleotide sequences, generating phylogenetic trees, or producing alignment output in various formats.

More results

Use when masking columns or coordinate ranges in multiple-sequence alignments before downstream HMMER or alignment-processing steps.

mantis-interleaved-multi-image-instruction-tuning-arxiv-2405

Mantis: Interleaved Multi-Image Instruction Tuning

Sequence and choreograph multi-step animations using GSAP timelines, including nesting, labels, position parameter, and playback control.

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

matryoshka-representation-learning-arxiv-2205-13147v4

Matryoshka Representation Learning

intense-visions

design-alignment

Perform nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised or semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows using the umap-learn library.

30.2k · bundle

Process and analyze mass spectrometry data: import spectra from MGF, mzML, MSP, and JSON formats; apply 40+ filters for metadata harmonization and peak cleaning; compute spectral similarities (cosine, modified cosine) for compound identification; build reproducible processing pipelines.

30.2k · bundle

moonladderstudios

Analyze and automatically remediate MoonSpec artifact inconsistencies across spec.md, plan.md, tasks.md, and related design files. Use when the user asks to run `/moonspec.align`, identify uncertainty, weigh tradeoffs in project context, edit artifacts without asking follow-up questions, resolve coverage gaps, or align generated MoonSpec documents before implementation.

muapi-multi-angle-reshoot

Re-renders a subject or scene from multiple dramatic camera angles while maintaining consistent identity and detail.

mosaic-augmentation-for-detection-and-segmentation-arxiv-yol

Mosaic Augmentation for Detection and Segmentation

lima-less-is-more-for-alignment-arxiv-2305-11206v1

LIMA: Less Is More for Alignment

multimodal-few-shot-learning-with-frozen-language-models-arx

Multimodal Few-Shot Learning with Frozen Language Models

visual-instruction-tuning-arxiv-2304-08485v2

Visual Instruction Tuning

metinduraktr-44

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

cogvlm-visual-expert-for-pretrained-language-models-arxiv-23

CogVLM: Visual Expert for Pretrained Language Models

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.

emu-generative-pretraining-in-multimodality-arxiv-2307-05222

Emu: Generative Pretraining in Multimodality

alterlab-matchms

Computes mass-spectral similarity and identifies compounds for metabolomics with matchms — comparing mass spectra, scoring similarity (cosine, modified cosine), and searching spectral libraries to annotate unknowns. Use when matching MS/MS spectra, identifying metabolites, or library searching; for full LC-MS/MS proteomics pipelines use pyopenms. Part of the AlterLab Academic Skills suite.

UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.

Use when performing pairwise structural alignments of RNA sequences that incorporate both sequence and structure information through base pair propensity vectors.

llava-next-improved-reasoning-ocr-and-world-knowledge-arxiv-

LLaVA-NeXT: Improved Reasoning, OCR, and World Knowledge

Use when aligning long FASTQ reads to a reference genome with Subread's long-read aligner, optionally in RNA-seq mode.

svit-scaling-up-visual-instruction-tuning-arxiv-2307-04087v2

SVIT: Scaling up Visual Instruction Tuning

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

copy-paste-augmentation-for-instance-segmentation-arxiv-2012

Copy-Paste Augmentation for Instance Segmentation

multimodal-neurons-in-artificial-neural-networks-arxiv-2103-

Multimodal Neurons in Artificial Neural Networks

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.

Use when evaluating the free energy (kcal/mol) of an RNA secondary structure, calculating co-folding energies for two RNA strands, or analyzing consensus structures from multiple sequence alignments.

Build and analyze phylogenetic trees using MAFFT, IQ-TREE 2, and FastTree, with visualization via ETE3 or FigTree for evolutionary analysis, microbial genomics, viral phylodynamics, and molecular clock studies.

30.2k · bundle