Results for “molecular-generation”

58 skills

Access AI-ready drug discovery datasets and benchmarks from Therapeutics Data Commons, covering ADME, toxicity, drug-target interactions, and molecular generation with standardized splits and evaluation metrics.

30.2k · bundle

Access AI-ready drug discovery datasets, benchmarks, and molecular oracles from Therapeutics Data Commons for therapeutic machine learning and pharmacological prediction.

Graph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, GAT, SchNet), 40+ datasets, for PyTorch-based ML on molecules, proteins, and biomedical graphs.

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.

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Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.

Simulates meiotic recombination to produce offspring genomes from parent pairs, modeling Mendelian segregation, de novo mutation, sex determination, trait inference, and clinical evaluation against a disease registry.

Generate, predict, and embed protein sequences and structures using ESM3, ESMC, and ESMFold2 with local or cloud inference.

30.2k · bundle

Applies physical principles to model biological systems, including protein folding, membrane transport, molecular forces, and neural signaling.

johnalbertini14-glitch

Generates structured VGL JSON for Bria FIBO models, giving deterministic control over objects, lighting, camera, composition, and style instead of natural language prompts.

message-generator

Multi-channel personalized message generation with 3 tiers of personalization

Build and train graph neural networks for drug discovery, protein modeling, and molecular science using PyTorch-native tools.

30.2k · bundle

sql-query-generation

Generate SQL queries from natural-language requirements using SELECT, JOIN, GROUP BY, window functions, CTEs, and subqueries. Use when the user needs a new query from a business question or schema; use query-optimization when an existing query or execution plan is slow.

algorithmic-art

Create algorithmic art by first writing a generative philosophy, then expressing it as p5.js sketches with seeded randomness and interactive parameter exploration.

nv-generate-mr-brain

Generates synthetic brain MRI volumes using NVIDIA's NV-Generate-CTMR workflow, with configurable modality and random seed.

Run machine learning and generative AI tasks directly in BigQuery SQL using built-in functions for forecasting, anomaly detection, key driver analysis, and text generation.

14.4k · bundle

code-testing-agent

Generates and writes unit tests for any programming language using a multi-agent pipeline that researches, plans, and implements tests with build and verification steps.

Atomic-design guidance for Molecules — functional groups of atoms (SearchBar = input + button + icon; FormField = label + input + error) with a single cohesive purpose. Use when authoring or reviewing components under ui/molecules, composing atoms, or deciding atom vs molecule vs organism.

Featurização molecular para ML (100+ featurizadores). ECFP, MACCS, descritores, modelos pré-treinados (ChemBERTa), converter SMILES em features, para QSAR e ML molecular.

Explains cellular structures, membrane transport, energetics, signaling, and division, connecting molecular events to organismal function.

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

molecular-dynamics

Run and analyze molecular dynamics simulations with OpenMM and MDAnalysis. Set up protein/small molecule systems, define force fields, run energy minimization and production MD, analyze trajectories (RMSD, RMSF, contact maps, free energy surfaces).

30.2k · bundle

Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework

Explains cell structure, organelles, signaling pathways, and cell cycle regulation for biology study and research.

Define every visual attribute as structured VGL JSON for deterministic, reproducible image generation with Bria FIBO models, covering objects, lighting, camera settings, composition, and style.

Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework

Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library

hypothesis-generation

Formulate testable hypotheses from observations, design experiments, and generate predictions using a structured scientific method framework.

30.2k · bundle

Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library

Generate realistic dummy datasets for testing with customizable columns, constraints, and output formats (CSV, JSON, SQL, Python script).

ai-music-generation

Generate music and songs using ElevenLabs, Diffrythm, and Tencent Song Generation models via the inference.sh CLI.

Molecular machine learning toolkit. Property prediction (ADMET, toxicity), GNNs (GCN, MPNN), MoleculeNet benchmarks, pretrained models, featurization, for drug discovery ML.

algorithmic-art

Creates algorithmic art with p5.js, starting from a generative philosophy and expressing it through seeded randomness, noise fields, and particle systems.

Outlines — structured generation with guaranteed JSON/regex output from local LLMs

code-generation

Automates Flutter code generation with build_runner, freezed, json_serializable, injectable, and auto_route, including setup, configuration, and command execution.

lucassantana-dev

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

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

30.2k · bundle