(oaftype exact result) and (resulttypeid exact software) en_US 10 1 1201228

RECOLECTA___::cd7d27937aac3f2f420f6ee699bec4b8 2026-10-23T10:51:34.674711713 2026-09-10T18:50:50.991604Z

50|RECOLECTA___::cd7d27937aac3f2f420f6ee699bec4b8 oai:dnet:ruarepositor::d2495e061de86b3e5ac101d328214050 10045/160915 Martinez-Martin, Ester Costa, Angelo Martinez-Martin, Ester|| Costa, Angelo|| Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial Repositorio Institucional de la Universidad de Alicante 2025-01-01 Plataforma web que aúna distintas herramientas para el reconocimiento y generación de LSE y LOE. Herramientas para comunicación Lengua de signos española instname:Universidad de Alicante (UA) reponame:RUA. Repositorio Institucional de la Universidad de Alicante application/octet-stream false false 0.9 null 2025-01-01 10045/160915 https://hdl.handle.net/10045/160915

__bioTools__::001a834a3affa8af00789697395d26e1 2026-10-23T10:51:43.544746487 2026-09-30T11:15:32.985Z

50|__bioTools__::001a834a3affa8af00789697395d26e1 bioconductor-rawrr Panse, Christian Kockmann, Tobias 2026-08-31 This package wraps the functionality of the Thermo Fisher Scientic RawFileReader .NET 8.0 assembly. Within the R environment, spectra and chromatograms are represented by S3 objects. The package provides basic functions to download and install the required third-party libraries. The package is developed, tested, and used at the Functional Genomics Center Zurich, Switzerland. bio.tools R https://bioconductor.org/packages/rawrr false false 0.9 2026-08-31 GPL https://bio.tools/bioconductor-rawrr

__bioTools__::0045f699cd8fa181a9c4c830ffcd3947 2026-10-23T10:51:41.363586558 2026-09-30T11:15:33.04Z

haste_toolkit 50|__bioTools__::0045f699cd8fa181a9c4c830ffcd3947 Blamey, Ben 2021-01-25 A collection of software components that can be used to build intelligent streaming pipelines for scientific data streams. 0202 electrical engineering, electronic engineering, information engineering 02 engineering and technology Computer science bio.tools false false 0.9 2021-01-25 https://bio.tools/haste_toolkit

__bioTools__::00e2c835d3ae2a8c80ecdbb68a721927 2026-10-23T10:51:47.312468267 2026-09-30T11:15:33.242Z

50|__bioTools__::00e2c835d3ae2a8c80ecdbb68a721927 findpromoter Team, Galaxy Support 2016-12-19 Program to search for a promoter motif and optionally, an adapter sequence from a source species on a target species. 0206 medical engineering Transcription factors and regulatory sites Sequence analysis 02 engineering and technology bio.tools https://galaxy.pasteur.fr/root?tool_id=toolshed.pasteur.fr%2Frepos%2Ffmareuil%2Fpromoteur_tools%2Ffindpromoter%2F1.0 false false 0.9 2016-12-19 https://bio.tools/findpromoter

__bioTools__::00e382e892d1c04c4f10e1670b12eebc 2026-10-23T10:51:44.764521737 2026-09-30T11:15:33.247Z

autosite 50|__bioTools__::00e382e892d1c04c4f10e1670b12eebc Sanner, Michel F. 2018-05-19 Computational method for identifying and characterizing small molecules binding sites for receptors of known three-dimensional structure. Binding sites are identified using energetic aspects to select high affinity points in space around the receptor, and a clustering technique for segregating these points into clusters called fills and corresponding to potential binding pockets. Protein binding sites Protein sites, features and motifs 0206 medical engineering 02 engineering and technology bio.tools Python http://adfr.scripps.edu/AutoDockFR/AutoSite_tutorial.pdf false false 0.9 doi_dedup___::a0062387197db31880495173b460c801 2016-06-26 <jats:title>Abstract</jats:title> <jats:p>Motivation: The identification of ligand-binding sites from a protein structure facilitates computational drug design and optimization, and protein function assignment. We introduce AutoSite: an efficient software tool for identifying ligand-binding sites and predicting pseudo ligand corresponding to each binding site identified. Binding sites are reported as clusters of 3D points called fills in which every point is labelled as hydroph PMC5048065 https://academic.oup.com/bioinformatics/article-pdf/32/20/3142/25040432/btw367.pdf https://academic.oup.com/bioinformatics/article-pdf/32/20/3142/25040432/btw367.pdf 2016-06-26 https://doi.org/10.1093/bioinformatics/btw367 https://doi.org/10.1093/bioinformatics/btw367 Pradeep Anand Ravindranath 2016-01-01 https://dblp.org/rec/journals/bioinformatics/RavindranathS16.html https://doi.org/10.1093/bioinformatics/btw367 https://dblp.org/rec/journals/bioinformatics/RavindranathS16.html https://doi.org/10.1093/bioinformatics/btw367 Oxford University Press (OUP) 2017-08-14 https://pubmed.ncbi.nlm.nih.gov/27354702 https://pubmed.ncbi.nlm.nih.gov/27354702 https://dx.doi.org/10.1093/bioinformatics/btw367 https://dx.doi.org/10.1093/bioinformatics/btw367 Michel F. Sanner 10.1093/bioinformatics/btw367 27354702 2018-05-19 https://bio.tools/autosite

__bioTools__::00ed53a666055a791bd5935e37e933ce 2026-10-23T10:51:29.633473358 2026-09-30T11:15:33.252Z

bottled_saft 50|__bioTools__::00ed53a666055a791bd5935e37e933ce Müller, E. A. 2018-05-29 SAFT-γ Mie Force Field Parameters for Thousands of Molecular Fluids. Chemistry Small molecules Molecular modelling bio.tools Python http://www.bottledsaft.org/about false false 0.9 2018-05-29 https://bio.tools/bottled_saft

__bioTools__::00fb81b0f860441c7d1a07f4031f7337 2026-10-23T10:51:46.369299088 2026-09-30T11:15:33.266Z

muscle-fascicle-tracking-ultrasound 50|__bioTools__::00fb81b0f860441c7d1a07f4031f7337 Lichtwark, Glen 2021-05-05 Implementation of an optical flow algorithm to track muscle length changes imaged with ultrasound. 0303 health sciences 03 medical and health sciences Biomedical science Echography Biology bio.tools MATLAB false false 0.9 2021-05-05 https://bio.tools/muscle-fascicle-tracking-ultrasound

__bioTools__::019813a398da665764643d79868e4bd3 2026-10-23T10:51:27.372732078 2026-09-30T11:15:33.439Z

pydockweb 50|__bioTools__::019813a398da665764643d79868e4bd3 Jiménez-Garcí­a, Brian Lumbreras, Luis Ángel Rodriguez 2016-10-11 Web server for the structural prediction of protein-protein interactions. Given the 3D coordinates of two interacting proteins, it returns the best rigid-body docking orientations generated by FTDock (Gabb HA. et al. J Mol Biol 1997;272:106-120) and evaluated by pyDock scoring function (Cheng et al. 2007 Proteins 68, 503-515), which includes electrostatics, desolvation energy and limited van der Waals contribution. Computational chemistry 0206 medical engineering 02 engineering and technology bio.tools https://life.bsc.es/pid/pydockweb/info/faq_and_help false false 0.9 doi_dedup___::b6807cfef2c2e17990326dd8645cf7b6 https://dx.doi.org/10.1093/bioinformatics/btt262 https://dx.doi.org/10.1093/bioinformatics/btt262 2013-12-17 https://pubmed.ncbi.nlm.nih.gov/23661696 https://pubmed.ncbi.nlm.nih.gov/23661696 2013-01-01 https://dblp.org/rec/journals/bioinformatics/Jimenez-GarciaPF13.html https://doi.org/10.1093/bioinformatics/btt262 https://dblp.org/rec/journals/bioinformatics/Jimenez-GarciaPF13.html https://doi.org/10.1093/bioinformatics/btt262 23661696 Juan Fernández-Recio Brian Jiménez-García Carles Pons https://academic.oup.com/bioinformatics/article-pdf/29/13/1698/18536412/btt262.pdf https://academic.oup.com/bioinformatics/article-pdf/29/13/1698/18536412/btt262.pdf <jats:title>Abstract</jats:title> <jats:p>Summary: pyDockWEB is a web server for the rigid-body docking prediction of protein–protein complex structures using a new version of the pyDock scoring algorithm. We use here a new custom parallel FTDock implementation, with adjusted grid size for optimal FFT calculations, and a new version of pyDock, which dramatically speeds up calculations while keeping the same predictive accuracy. Given the 3D coordinates of two interacting proteins, Oxford University Press (OUP) 2013-05-09 10.1093/bioinformatics/btt262 2013-05-09 https://doi.org/10.1093/bioinformatics/btt262 https://doi.org/10.1093/bioinformatics/btt262 doi_dedup___::b6807cfef2c2e17990326dd8645cf7b6 https://dx.doi.org/10.1093/bioinformatics/btt262 https://dx.doi.org/10.1093/bioinformatics/btt262 2013-12-17 https://pubmed.ncbi.nlm.nih.gov/23661696 https://pubmed.ncbi.nlm.nih.gov/23661696 2013-01-01 https://dblp.org/rec/journals/bioinformatics/Jimenez-GarciaPF13.html https://doi.org/10.1093/bioinformatics/btt262 https://dblp.org/rec/journals/bioinformatics/Jimenez-GarciaPF13.html https://doi.org/10.1093/bioinformatics/btt262 23661696 Juan Fernández-Recio Brian Jiménez-García Carles Pons https://academic.oup.com/bioinformatics/article-pdf/29/13/1698/18536412/btt262.pdf https://academic.oup.com/bioinformatics/article-pdf/29/13/1698/18536412/btt262.pdf <jats:title>Abstract</jats:title> <jats:p>Summary: pyDockWEB is a web server for the rigid-body docking prediction of protein–protein complex structures using a new version of the pyDock scoring algorithm. We use here a new custom parallel FTDock implementation, with adjusted grid size for optimal FFT calculations, and a new version of pyDock, which dramatically speeds up calculations while keeping the same predictive accuracy. Given the 3D coordinates of two interacting proteins, Oxford University Press (OUP) 2013-05-09 10.1093/bioinformatics/btt262 2013-05-09 https://doi.org/10.1093/bioinformatics/btt262 https://doi.org/10.1093/bioinformatics/btt262 2016-10-11 https://bio.tools/pydockweb

__bioTools__::01b68f18b3e3b3977837aa3fc2ca37fd 2026-10-23T10:51:39.569026353 2026-09-30T11:15:33.463Z

50|__bioTools__::01b68f18b3e3b3977837aa3fc2ca37fd msacquisitionsimulator Wang W MB, Major 2017-08-03 Collection of three command-line tools that simulate data-dependent acquisition algorithms on in silico generated ground truth data of liquid chromatography-mass spectrometry proteomics experiments. Proteomics Simulation experiment Proteomics experiment bio.tools C++ https://github.com/UNC-Major-Lab/MSAcquisitionSimulator/blob/master/README.md false false 0.9 2017-08-03 https://bio.tools/msacquisitionsimulator

__bioTools__::01eb68abd5b2810d956d1ca57a0bab03 2026-10-23T10:51:37.991507525 2026-09-30T11:15:33.499Z

biojs-model 50|__bioTools__::01eb68abd5b2810d956d1ca57a0bab03 BioJS 2015-01-22 Biological data models. Bioinformatics 0206 medical engineering 02 engineering and technology bio.tools JavaScript https://github.com/biojs/biojs-model false false 0.9 2015-01-22 https://bio.tools/biojs-model