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Química Computacional

Explora habilidades de agente para simulaciones moleculares, descubrimiento de fármacos, análisis ADME y screening de compuestos químicos

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23.259 resultados

ruview-advanced-sensing

Fuenteruvnet/RuView/plugins/ruview/skills/ruview-advanced-sensing/SKILL.md
Actualizado

Advanced RuView capabilities — RuvSense multistatic sensing (attention-weighted fusion, geometric diversity, persistent field model), cross-viewpoint fusion across multiple nodes, RF tomography (ISTA L1 solver, voxel grids), longitudinal biomechanics drift, pre-movement intention signals, adversarial signal detection, and multistatic mesh security hardening. Use for research-grade or multi-node deployments.

Idioma del contenido del Skill: inglés

ruview-applications

Fuenteruvnet/RuView/plugins/ruview/skills/ruview-applications/SKILL.md
Actualizado

Run RuView sensing applications — presence/occupancy, breathing & heart rate, activity & fall detection, 17-keypoint pose estimation (WiFlow), sleep monitoring & apnea screening, environment mapping, Mass Casualty Assessment (MAT), and the 3D point-cloud fusion demo. Use when someone wants to actually *do* something with a working RuView setup.

Idioma del contenido del Skill: inglés

ruview-mmwave

Fuenteruvnet/RuView/plugins/ruview/skills/ruview-mmwave/SKILL.md
Actualizado

Set up and run RuView mmWave / FMCW radar sensing — ESP32-C6 + Seeed MR60BHA2 (60 GHz, heart rate / breathing rate / presence) and HLK-LD2410 (24 GHz, presence + distance), plus mmWave↔WiFi-CSI sensor fusion (48-byte fused vitals, MR60BHA2/LD2410 auto-detect, v0.5.0+). Use when the deployment includes a millimetre-wave radar alongside or instead of WiFi CSI.

Idioma del contenido del Skill: inglés

adaptyv

FuenteK-Dense-AI/scientific-agent-skills/skills/adaptyv/SKILL.md
Actualizado

Uses the Adaptyv Bio Foundry API and Python SDK to design protein characterization experiments, estimate costs, submit sequences, monitor laboratory progress, and retrieve results. Applies to Adaptyv Foundry, its target catalog, binding screening and affinity assays, thermostability, expression, fluorescence, epitope binning, and enzyme activity workflows, including code using adaptyv or FoundryClient.

Idioma del contenido del Skill: inglés

mageck

FuenteK-Dense-AI/scientific-agent-skills/skills/mageck/SKILL.md
Actualizado

Analyzes pooled CRISPR screen FASTQ reads and guide-count matrices with MAGeCK, validates guide libraries and contrasts, measures replicate and library QC, and produces gene hit rankings with effect sizes and FDR. Use for new knockout, CRISPRi, or CRISPRa screen analysis, enrichment or depletion contrasts, and MAGeCK count/test workflows; existing public dependency-score lookup belongs to DepMap.

Idioma del contenido del Skill: inglés

openpiv

FuenteK-Dense-AI/scientific-agent-skills/skills/openpiv/SKILL.md
Actualizado

Performs Particle Image Velocimetry (PIV) analysis with OpenPIV. Use when extracting velocity fields from PIV image pairs, analyzing fluid dynamics or flow visualization experiments, cross-correlating interrogation windows, validating and replacing spurious PIV vectors, or computing vorticity, strain rate, and turbulence statistics from measured velocity fields.

Idioma del contenido del Skill: inglés

pkpd-modeling

FuenteK-Dense-AI/scientific-agent-skills/skills/pkpd-modeling/SKILL.md
Actualizado

Pharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".

Idioma del contenido del Skill: inglés

primer-design

FuenteK-Dense-AI/scientific-agent-skills/skills/primer-design/SKILL.md
Actualizado

Designs and audits PCR and RT-qPCR primers with Primer3, explicit thermodynamic conditions, reference-based off-target amplification searches, and traceable sequence coordinates. Use for designing primer pairs, checking existing primers, exon-junction or isoform-specific assays, variant masking, cloning tails, multiplex compatibility, and interpreting Primer-BLAST results. Includes bounded local in-silico PCR and BLAST screening; distinguishes computational candidates from experimentally validated assays.

Idioma del contenido del Skill: inglés

rowan

FuenteK-Dense-AI/scientific-agent-skills/skills/rowan/SKILL.md
Actualizado

Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.

Idioma del contenido del Skill: inglés

tellurium

FuenteK-Dense-AI/scientific-agent-skills/skills/tellurium/SKILL.md
Actualizado

Simulates biochemical kinetic models from SBML or Antimony with Tellurium and libRoadRunner, checks model units, compares deterministic parameter perturbations, and exports and replays SBML plus SED-ML COMBINE archives. Use for reaction-network time courses, kinetic parameters, concentration dynamics and reproducible simulation experiments; steady-state constraint-based metabolic flux analysis belongs to cobrapy.

Idioma del contenido del Skill: inglés

pixijs-scene-particle-container

Fuentepixijs/pixijs/skills/pixijs-scene-particle-container/SKILL.md
Actualizado

Use this skill when rendering thousands of lightweight sprites in PixiJS v8. Covers ParticleContainer with Particle instances, addParticle/removeParticle, particleChildren array, dynamicProperties (vertex, position, rotation, uvs, color), boundsArea, roundPixels, update, inherited alpha/tint/blendMode from ancestors. Triggers on: ParticleContainer, Particle, IParticle, addParticle, particleChildren, dynamicProperties, boundsArea, particle effects, particle alpha, particle tint, fade particles, constructor options, ParticleContainerOptions, ParticleOptions.

Idioma del contenido del Skill: inglés

math-olympiad

Fuenteanthropics/claude-plugins-official/plugins/math-olympiad/skills/math-olympiad/SKILL.md
Actualizado

Solve competition math problems (IMO, Putnam, USAMO, AIME) with adversarial verification that catches the errors self-verification misses. Activates when asked to 'solve this IMO problem', 'prove this olympiad inequality', 'verify this competition proof', 'find a counterexample', 'is this proof correct', or for any problem with 'IMO', 'Putnam', 'USAMO', 'olympiad', or 'competition math' in it. Uses pure reasoning (no tools) — then a fresh-context adversarial verifier attacks the proof using specific failure patterns, not generic 'check logic'. Outputs calibrated confidence — will say 'no confident solution' rather than bluff. If LaTeX is available, produces a clean PDF after verification passes.

Idioma del contenido del Skill: inglés

analyzing-campaign-attribution-evidence

Fuentemukul975/Anthropic-Cybersecurity-Skills/skills/analyzing-campaign-attribution-evidence/SKILL.md
Actualizado

Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

Idioma del contenido del Skill: inglés