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BioTSR 1.0.0

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@pooryakhajouie pooryakhajouie released this 26 Oct 16:26
· 5 commits to main since this release
v1.0.0
a068c99

BioTSR 1.0.0 is the first release of BioTSR, the unified software implementation of the Triangular Spatial Relationship (TSR) methodology: one Python package, one command line and one shared scientific core, the TSR Engine, in place of a family of independent historical TSR programs. Every method runs under one standard profile and writes one self-describing output format.

Install

From PyPI (https://pypi.org/project/biotsr/1.0.0/):

pip install biotsr==1.0.0

The files on PyPI are the ones attached below, byte for byte (same SHA-256), published from this tag through Trusted Publishing with provenance attestations. Or from GitHub:

pip install "biotsr @ git+https://github.com/TSRMethod/BioTSR@v1.0.0"

Supported: CPython 3.9–3.13 on Linux and macOS. Windows is not supported. One runtime dependency (joblib); the optional plot extra adds matplotlib for the clustered heat map.

Highlights

  • Twenty methods — protein Cα; atomic (amino-acid, ligand, carbohydrate, nucleotide/DNA/RNA, residue and atom selections); five cross (two-sided) methods.
  • Composable modifiers — amino-acid grouping and SSE-TSR (18 categories) on Cα methods, mirror signing, size filtering.
  • Labels — Cα residues at radix 30 including eleven modified residues; atoms by PDB element field at radix 112.
  • Strict input rules — nothing guessed; unknown residues, missing elements, duplicate atoms and unreadable residue numbers in a selection are refused by name.
  • Two fingerprints on every result — results whose keys mean different things are never combined.
  • Datasets — manifests and wide sheets, dry runs, verified resuming, parallel rows, opt-in verified PDB download.
  • Analysis — feature matrices, common keys, similarity measures, average-linkage clustering and heat map.

Full notes: CHANGELOG.md · Known limitations: docs/KNOWN_LIMITATIONS.md · User guide: docs/USER_GUIDE.md

Validation

Tested on every supported Python on Linux (x86-64) and macOS (arm64); the slow standard reference cases and the release checks ran on macOS arm64 on the tagged commit (a068c99). The attached manifest records the commit, the label-table and key-space fingerprints, the reference runs and the artifact hashes.

Files

file SHA-256
biotsr-1.0.0-py3-none-any.whl ba6afa1f6a1bef4314fedc4786aa862558e82b15d06e3e3b1123bfbd76e20cea
biotsr-1.0.0.tar.gz 99a827fa5e642c14154d656e48dda76fc09a1518c312f7379c7996b24a2ec74a
RELEASE_CANDIDATE_MANIFEST.json 5cbef73b6a22d25bd285031e48ae5f0e81664c384f9de02e522e82d47509e4d9 — release manifest
RELEASE_ARTIFACTS.json dc164094a1d7d00b79e2d5121cf293624af6db00f3f410a60a535217e9fcda94 — build, inspection and clean-install report

All four come from release validation run 40248104783 on the tagged commit a068c99.

Citation

Please cite BioTSR using CITATION.cff ("Cite this repository" on the repository page):

Khajouie, P., Rauniyar, K., Raghavan, V. V., & Xu, W. BioTSR (version 1.0.0) [Computer software]. https://github.com/TSRMethod/BioTSR

Licensed under the Apache License 2.0; third-party notices are in NOTICE.

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