Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
日本語の概要は準備中です。原文の説明を表示しています。
Use Biotite for computational molecular biology workflows: sequence analysis, structure analysis, biological database access, file-format conversion, application wrappers, and optional molecular interfaces.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Use this repo skill when a task involves Biotite, biotite.sequence, biotite.structure, biological sequence/structure files, RCSB/Entrez/UniProt/PubChem/AlphaFold DB access, external bioinformatics application wrappers, or optional PyMOL/RDKit/OpenMM/Matplotlib integration.
Biotite is a Python package for computational molecular biology. It represents sequences and molecular structures with NumPy-backed objects and exposes APIs for file parsing, local analysis, database queries, visualization, and external tool orchestration.
For normal package use, prefer wheel installs:
python -m pip install biotite
python - <<'PY'
import biotite
import biotite.sequence as seq
import biotite.structure as struc
print(biotite.__version__)
print(seq.ProteinSequence("ACDE"))
print(struc.AtomArray(1).array_length())
PY
For source checkouts, Biotite may need Python 3.12+, NumPy, Cython/build tooling, Rust build support, and compiled extension wheels. Prefer wheel installs for use-only tasks and source installs only for development or unreleased APIs.
Run the bundled diagnostic when routing a user problem:
python scripts/check_biotite_environment.py
It performs import/version checks and can also call the sub-skill optional diagnostics without contacting networks or running analyses.
Atom, AtomArray, AtomArrayStack, filters, bonds, geometry, superposition, RMSD/RMSF, SASA, hydrogen bonds, base pairs, pseudoknots, periodic boxes, secondary structure, and trajectory analysis.database-application for Entrez/UniProt/RCSB retrieval, file-io-formats for FASTA/GenBank parsing, then sequence-analysis for alignment/profile/phylogeny.database-application for RCSB/AFDB fetch if needed, file-io-formats for PDBx/BinaryCIF parsing, then structure-analysis for filtering, bonds, geometry, SASA, contacts, or superposition.file-io-formats for MOL/SDF/PDBx loading, structure-analysis to prepare coordinates/bonds, then interfaces-visualization for RDKit/OpenMM/PyMOL/plotting.database-application first to check binaries and wrapper lifecycle; route outputs to file-io-formats, sequence-analysis, or structure-analysis.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
日本語の概要は準備中です。原文の説明を表示しています。
Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.
日本語の概要は準備中です。原文の説明を表示しています。
Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.
日本語の概要は準備中です。原文の説明を表示しています。
Use Hugging Face Accelerate for PyTorch training-loop migration, distributed launch/configuration, DeepSpeed/FSDP/TPU backend setup, big-model inference/offload, checkpointing, tracking, and troubleshooting.
日本語の概要は準備中です。原文の説明を表示しています。
Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
日本語の概要は準備中です。原文の説明を表示しています。