Pykvfinder

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0.6.10

Python-C parallel KVFinder

The Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities (shape, volume, area, depth, openings [WIP], hydropathy, and interface residues and their frequencies) in target biomolecular structures using a dual-probe system. In addition to cavity detection, pyKVFinder also estimates the molecular volume, using van der Waals (vdW) surface, solvent excluded surface (SES), and solvent accessible surface (SAS) to represent the molecular surface.

Python package

The pyKVFinder package is easily imported into Python scripts with a set of functions that enables full and standard workflows and step-by-step analysis.

Command-line interface

The integrated command-line interface performs cavity detection and characterization with a customizable set of parameters. The standard characterization includes shape, volume, area, and interface residues and their frequencies. The optional characterizations are depth (per cavity point, maximum and average) and hydropathy (per surface point and average) with six options of built-in hydrophobicity scales (EisenbergWeiss, HessaHeijne, KyteDoolittle, MoonFleming, RadzickaWolfenden, WimleyWhite, and ZhaoLondon).

What's Changed
* [MNT] Add Windows build support to pyKVFinder by wapablos and jvsguerra in https://github.com/LBC-LNBio/pyKVFinder/pull/73


**Full Changelog**: https://github.com/LBC-LNBio/pyKVFinder/compare/v0.6.9...v0.6.10

0.6.9

Python-C parallel KVFinder

The Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities (shape, volume, area, depth, openings [WIP], hydropathy, and interface residues and their frequencies) in target biomolecular structures using a dual-probe system. In addition to cavity detection, pyKVFinder also estimates the molecular volume, using van der Waals (vdW) surface, solvent excluded surface (SES), and solvent accessible surface (SAS) to represent the molecular surface.

Python package

The pyKVFinder package is easily imported into Python scripts with a set of functions that enables full and standard workflows and step-by-step analysis.

Command-line interface

The integrated command-line interface performs cavity detection and characterization with a customizable set of parameters. The standard characterization includes shape, volume, area, and interface residues and their frequencies. The optional characterizations are depth (per cavity point, maximum and average) and hydropathy (per surface point and average) with six options of built-in hydrophobicity scales (EisenbergWeiss, HessaHeijne, KyteDoolittle, MoonFleming, RadzickaWolfenden, WimleyWhite, and ZhaoLondon).

What's Changed
* Bump black from 23.10.1 to 23.11.0 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/69
* Bump numpy from 1.26.1 to 1.26.2 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/70
* Bump matplotlib from 3.7.3 to 3.8.2 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/71


**Full Changelog**: https://github.com/LBC-LNBio/pyKVFinder/compare/v0.6.8...v0.6.9

0.6.8

Python-C parallel KVFinder

The Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities (shape, volume, area, depth, openings [WIP], hydropathy, and interface residues and their frequencies) in target biomolecular structures using a dual-probe system. In addition to cavity detection, pyKVFinder also estimates the molecular volume, using van der Waals (vdW) surface, solvent excluded surface (SES), and solvent accessible surface (SAS) to represent the molecular surface.

Python package

The pyKVFinder package is easily imported into Python scripts with a set of functions that enables full and standard workflows and step-by-step analysis.

Command-line interface

The integrated command-line interface performs cavity detection and characterization with a customizable set of parameters. The standard characterization includes shape, volume, area, and interface residues and their frequencies. The optional characterizations are depth (per cavity point, maximum and average) and hydropathy (per surface point and average) with six options of built-in hydrophobicity scales (EisenbergWeiss, HessaHeijne, KyteDoolittle, MoonFleming, RadzickaWolfenden, WimleyWhite, and ZhaoLondon).

What's Changed
* Bump numpy from 1.26.0 to 1.26.1 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/63
* Bump black from 23.9.1 to 23.10.1 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/65
* Bump pytest from 7.4.2 to 7.4.3 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/66
* Bump plotly from 5.17.0 to 5.18.0 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/67

**Full Changelog**: https://github.com/LBC-LNBio/pyKVFinder/compare/v0.6.7...v0.6.8

0.6.7

Python-C parallel KVFinder

The Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities (shape, volume, area, depth, openings [WIP], hydropathy, and interface residues and their frequencies) in target biomolecular structures using a dual-probe system. In addition to cavity detection, pyKVFinder also estimates the molecular volume, using van der Waals (vdW) surface, solvent excluded surface (SES), and solvent accessible surface (SAS) to represent the molecular surface.

Python package

The pyKVFinder package is easily imported into Python scripts with a set of functions that enables full and standard workflows and step-by-step analysis.

Command-line interface

The integrated command-line interface performs cavity detection and characterization with a customizable set of parameters. The standard characterization includes shape, volume, area, and interface residues and their frequencies. The optional characterizations are depth (per cavity point, maximum and average) and hydropathy (per surface point and average) with six options of built-in hydrophobicity scales (EisenbergWeiss, HessaHeijne, KyteDoolittle, MoonFleming, RadzickaWolfenden, WimleyWhite, and ZhaoLondon).

What's Changed
* Update Issues templates with .yml forms by jvsguerra in https://github.com/LBC-LNBio/pyKVFinder/pull/60
* Update pyKVFinderResults docstring and documentation by jvsguerra in https://github.com/LBC-LNBio/pyKVFinder/pull/62

**Full Changelog**: https://github.com/LBC-LNBio/pyKVFinder/compare/v0.6.6...v0.6.7

0.6.6

Python-C parallel KVFinder

The Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities (shape, volume, area, depth, openings [WIP], hydropathy, and interface residues and their frequencies) in target biomolecular structures using a dual-probe system. In addition to cavity detection, pyKVFinder also estimates the molecular volume, using van der Waals (vdW) surface, solvent excluded surface (SES), and solvent accessible surface (SAS) to represent the molecular surface.

Python package

The pyKVFinder package is easily imported into Python scripts with a set of functions that enables full and standard workflows and step-by-step analysis.

Command-line interface

The integrated command-line interface performs cavity detection and characterization with a customizable set of parameters. The standard characterization includes shape, volume, area, and interface residues and their frequencies. The optional characterizations are depth (per cavity point, maximum and average) and hydropathy (per surface point and average) with six options of built-in hydrophobicity scales (EisenbergWeiss, HessaHeijne, KyteDoolittle, MoonFleming, RadzickaWolfenden, WimleyWhite, and ZhaoLondon).

**Full Changelog**: https://github.com/LBC-LNBio/pyKVFinder/compare/v0.6.5...v0.6.6

0.6.5

Python-C parallel KVFinder

The Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities (shape, volume, area, depth, openings [WIP], hydropathy, and interface residues and their frequencies) in target biomolecular structures using a dual-probe system. In addition to cavity detection, pyKVFinder also estimates the molecular volume, using van der Waals (vdW) surface, solvent excluded surface (SES), and solvent accessible surface (SAS) to represent the molecular surface.

Python package

The pyKVFinder package is easily imported into Python scripts with a set of functions that enables full and standard workflows and step-by-step analysis.

Command-line interface

The integrated command-line interface performs cavity detection and characterization with a customizable set of parameters. The standard characterization includes shape, volume, area, and interface residues and their frequencies. The optional characterizations are depth (per cavity point, maximum and average) and hydropathy (per surface point and average) with six options of built-in hydrophobicity scales (EisenbergWeiss, HessaHeijne, KyteDoolittle, MoonFleming, RadzickaWolfenden, WimleyWhite, and ZhaoLondon).

What's Changed
* Bump pytest from 7.4.0 to 7.4.2 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/53
* Bump black from 23.7.0 to 23.9.1 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/54
* Bump plotly from 5.16.1 to 5.17.0 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/56
* Bump matplotlib from 3.7.2 to 3.8.0 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/57
* Bump numpy from 1.25.2 to 1.26.0 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/58


**Full Changelog**: https://github.com/LBC-LNBio/pyKVFinder/compare/v0.6.4...v0.6.5

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