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Metabolomic signatures represent a robust molecular framework for elucidating cancer-associated biochemical reprogramming. The use of Artificial Intelligence (AI) in biology in recent years has become widespread and promising. This study introduces a novel predictive method that integrates an Autoencoder, random forest based feature selection and Tabular Prior-data Fitted Network (TabPFN) to achieve high diagnostic accuracy from metabolomics data of prostate and breast cancer patients.", "homepage": "https://github.com/SvenHauns/metabolomic_classifier.git", "biotoolsID": "autoencoder_rf_tabpfn_for_cross-cancer_metabolomics", "biotoolsCURIE": "biotools:autoencoder_rf_tabpfn_for_cross-cancer_metabolomics", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2990", "term": "Classification" } ], "input": [], "output": [], "note": null, "cmd": "python main.py --dataset {dataset_to_be_used} --setting {ae or rf} --size {size}\n\npython main.py --test_dataset {./data/toy_predict.csv} --dataset {./data/toy_train.csv} --predict True --setting {ae or rf} --size {size}\n\nsee Readme for detailed instructions" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_2815", "term": "Human biology" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" } ], "operatingSystem": [], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/SvenHauns/metabolomic_classifier.git", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/SvenHauns/metabolomic_classifier.git", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/SvenHauns/metabolomic_classifier.git", "type": [ "User manual" ], "note": null } ], "publication": [], "credit": [ { "name": "Sven Hauns", "email": "haunss@informatik.uni-freiburg.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "haunssv", "additionDate": "2026-03-30T13:34:06.425220Z", "lastUpdate": "2026-03-30T13:34:06.427392Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Gromacs", "description": "Versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. It is primarily designed for biochemical molecules like proteins, lipids and nucleic acids that have a lot of complicated bonded interactions, but since it is extremely fast at calculating the nonbonded interactions (that usually dominate simulations) many groups are also using it for research on non-biological systems, e.g. polymers.", "homepage": "http://www.gromacs.org/", "biotoolsID": "gromacs", "biotoolsCURIE": "biotools:gromacs", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2476", "term": "Molecular dynamics" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0883", "term": "Structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Library", "Suite" ], "topic": [ { "uri": "http://edamontology.org/topic_0176", "term": "Molecular dynamics" } ], "operatingSystem": [ "Linux" ], "language": [], "license": "LGPL-2.1", "collectionID": [ "BioExcel" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "http://www.gromacs.org/Downloads", "type": "Software package", "note": null, "version": null } ], "documentation": [ { "url": "http://www.gromacs.org/Documentation", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1016/j.softx.2015.06.001", "pmid": null, "pmcid": null, "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "Gromacs: High performance molecular simulations through multi-level parallelism from laptops to supercomputers", "abstract": "GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules. It provides a rich set of calculation types, preparation and analysis tools. Several advanced techniques for free-energy calculations are supported. In version 5, it reaches new performance heights, through several new and enhanced parallelization algorithms. These work on every level; SIMD registers inside cores, multithreading, heterogeneous CPU-GPU acceleration, state-of-the-art 3D domain decomposition, and ensemble-level parallelization through built-in replica exchange and the separate Copernicus framework. The latest best-in-class compressed trajectory storage format is supported.", "date": "2015-01-01T00:00:00Z", "citationCount": 15418, "authors": [ { "name": "Abraham M.J." }, { "name": "Murtola T." }, { "name": "Schulz R." }, { "name": "Pall S." }, { "name": "Smith J.C." }, { "name": "Hess B." }, { "name": "Lindah E." } ], "journal": "SoftwareX" } }, { "doi": "10.1002/jcc.20291", "pmid": "16211538", "pmcid": null, "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "GROMACS: Fast, flexible, and free", "abstract": "This article describes the software suite GROMACS (Groningen MAchine for Chemical Simulation) that was developed at the University of Groningen, The Netherlands, in the early 1990s. The software, written in ANSI C, originates from a parallel hardware project, and is well suited for parallelization on processor clusters. By careful optimization of neighbor searching and of inner loop performance, GROMACS is a very fast program for molecular dynamics simulation. It does not have a force field of its own, but is compatible with GROMOS, OPLS, AMBER, and ENCAD force fields. In addition, it can handle polarizable shell models and flexible constraints. The program is versatile, as force routines can be added by the user, tabulated functions can be specified, and analyses can be easily customized. Nonequilibrium dynamics and free energy determinations are incorporated. Interfaces with popular quantum-chemical packages (MOPAC, GAMES-UK, GAUSSIAN) are provided to perform mixed MM/QM simulations. The package includes about 100 utility and analysis programs. GROMACS is in the public domain and distributed (with source code and documentation) under the GNU General Public License. It is maintained by a group of developers from the Universities of Groningen, Uppsala, and Stockholm, and the Max Planck Institute for Polymer Research in Mainz. Its Web site is http://www.gromacs.org. © 2005 Wiley Periodicals, Inc.", "date": "2005-12-01T00:00:00Z", "citationCount": 14137, "authors": [ { "name": "Van Der Spoel D." }, { "name": "Lindahl E." }, { "name": "Hess B." }, { "name": "Groenhof G." }, { "name": "Mark A.E." }, { "name": "Berendsen H.J.C." } ], "journal": "Journal of Computational Chemistry" } }, { "doi": "10.1063/5.0018516", "pmid": "33032406", "pmcid": null, "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "Heterogeneous parallelization and acceleration of molecular dynamics simulations in GROMACS", "abstract": "The introduction of accelerator devices such as graphics processing units (GPUs) has had profound impact on molecular dynamics simulations and has enabled order-of-magnitude performance advances using commodity hardware. To fully reap these benefits, it has been necessary to reformulate some of the most fundamental algorithms, including the Verlet list, pair searching, and cutoffs. Here, we present the heterogeneous parallelization and acceleration design of molecular dynamics implemented in the GROMACS codebase over the last decade. The setup involves a general cluster-based approach to pair lists and non-bonded pair interactions that utilizes both GPU and central processing unit (CPU) single instruction, multiple data acceleration efficiently, including the ability to load-balance tasks between CPUs and GPUs. The algorithm work efficiency is tuned for each type of hardware, and to use accelerators more efficiently, we introduce dual pair lists with rolling pruning updates. Combined with new direct GPU-GPU communication and GPU integration, this enables excellent performance from single GPU simulations through strong scaling across multiple GPUs and efficient multi-node parallelization.", "date": "2020-10-07T00:00:00Z", "citationCount": 349, "authors": [ { "name": "Pall S." }, { "name": "Zhmurov A." }, { "name": "Bauer P." }, { "name": "Abraham M." }, { "name": "Lundborg M." }, { "name": "Gray A." }, { "name": "Hess B." }, { "name": "Lindahl E." } ], "journal": "Journal of Chemical Physics" } }, { "doi": "10.1007/978-3-319-15976-8_1", "pmid": null, "pmcid": null, "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "Tackling exascale software challenges in molecular dynamics simulations with GROMACS", "abstract": "GROMACS is a widely used package for biomolecular simulation, and over the last two decades it has evolved from small-scale efficiency to advanced heterogeneous acceleration and multi-level parallelism targeting some of the largest supercomputers in the world. Here, we describe some of the ways we have been able to realize this through the use of parallelization on all levels, combined with a constant focus on absolute performance. Release 4.6 of GROMACS uses SIMD acceleration on a wide range of architectures, GPU offloading acceleration, and both OpenMP and MPI parallelism within and between nodes, respectively. The recent work on acceleration made it necessary to revisit the fundamental algorithms of molecular simulation, including the concept of neighborsearching, and we discuss the present and future challenges we see for exascale simulation - in particular a very fine-grained task parallelism. We also discuss the software management, code peer review and continuous integration testing required for a project of this complexity.", "date": "2015-01-01T00:00:00Z", "citationCount": 752, "authors": [ { "name": "Pall S." }, { "name": "Abraham M.J." }, { "name": "Kutzner C." }, { "name": "Hess B." }, { "name": "Lindahl E." } ], "journal": "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)" } }, { "doi": "10.1093/bioinformatics/btt055", "pmid": "23407358", "pmcid": "PMC3605599", "type": [], "version": null, "note": null, "metadata": { "title": "GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit", "abstract": "Motivation: Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources.Results: Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations. © 2013 The Author. Published by Oxford University Press. All rights reserved.", "date": "2013-04-01T00:00:00Z", "citationCount": 5927, "authors": [ { "name": "Pronk S." }, { "name": "Pall S." }, { "name": "Schulz R." }, { "name": "Larsson P." }, { "name": "Bjelkmar P." }, { "name": "Apostolov R." }, { "name": "Shirts M.R." }, { "name": "Smith J.C." }, { "name": "Kasson P.M." }, { "name": "Van Der Spoel D." }, { "name": "Hess B." }, { "name": "Lindahl E." } ], "journal": "Bioinformatics" } }, { "doi": "10.1021/ct700301q", "pmid": "26620784", "pmcid": null, "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "GRGMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation", "abstract": "Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems. Here, we present a new implementation of our molecular simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines. The code encompasses a minimal-communication domain decomposition algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel. To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addition used a Multiple-Program, Multiple-Data approach, with separate node domains responsible for direct and reciprocal space interactions. Not only does this combination of algorithms enable extremely long simulations of large systems but also it provides that simulation performance on quite modest numbers of standard cluster nodes. © 2008 American Chemical Society.", "date": "2008-03-01T00:00:00Z", "citationCount": 13627, "authors": [ { "name": "Hess B." }, { "name": "Kutzner C." }, { "name": "Van Der Spoel D." }, { "name": "Lindahl E." } ], "journal": "Journal of Chemical Theory and Computation" } }, { "doi": "10.1007/s008940100045", "pmid": null, "pmcid": null, "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "GROMACS 3.0: A package for molecular simulation and trajectory analysis", "abstract": "GROMACS 3.0 is the latest release of a versatile and very well optimized package for molecular simulation. Much effort has been devoted to achieving extremely high performance on both workstations and parallel computers. The design includes an extraction of virial and periodic boundary conditions from the loops over pairwise interactions, and special software routines to enable rapid calculation of x-1/2. Inner loops are generated automatically in C or Fortran at compile time, with optimizations adapted to each architecture. Assembly loops using SSE and 3DNow! Multimedia instructions are provided for x86 processors, resulting in exceptional performance on inexpensive PC workstations. The interface is simple and easy to use (no scripting language), based on standard command line arguments with self-explanatory functionality and integrated documentation. All binary files are independent of hardware endian and can be read by versions of GROMACS compiled using different floating-point precision. A large collection of flexible tools for trajectory analysis is included, with output in the form of finished Xmgr/Grace graphs. A basic trajectory viewer is included, and several external visualization tools can read the GROMACS trajectory format.", "date": "2001-12-01T00:00:00Z", "citationCount": 6227, "authors": [ { "name": "Lindahl E." }, { "name": "Hess B." }, { "name": "van der Spoel D." } ], "journal": "Journal of Molecular Modeling" } }, { "doi": "10.1016/0010-4655(95)00042-E", "pmid": null, "pmcid": null, "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "GROMACS: A message-passing parallel molecular dynamics implementation", "abstract": "A parallel message-passing implementation of a molecular dynamics (MD) program that is useful for bio(macro)molecules in aqueous environment is described. The software has been developed for a custom-designed 32-processor ring GROMACS (GROningen MAchine for Chemical Simulation) with communication to and from left and right neighbours, but can run on any parallel system onto which a a ring of processors can be mapped and which supports PVM-like block send and receive calls. The GROMACS software consists of a preprocessor, a parallel MD and energy minimization program that can use an arbitrary number of processors (including one), an optional monitor, and several analysis tools. The programs are written in ANSI C and available by ftp (information: gromacs@chem.rug.nl) The functionality is based on the GROMOS (GROningen MOlecular Simulation) package (van Gunsteren and Berendsen, 1987; BIOMOS B.V., Nijenborgh 4, 9747 AG Groningen). Conversion programs between GROMOS and GROMACS formats are included. The MD program can handle rectangular periodic boundary conditions with temperature and pressure scaling. The interactions that can be handled without modification are variable non-bonded pair interactions with Coulomb and Lennard-Jones or Buckingham potentials, using a twin-range cut-off based on charge groups, and fixed bonded interactions of either harmonic or constraint type for bonds and bond angles and either periodic or cosine power series interactions for dihedral angles. Special forces can be added to groups of particles (for non-equilibrium dynamics or for position restraining) or between particles (for distance restraints). The parallelism is based on particle decomposition. Interprocessor communication is largely limited to position and force distribution over the ring once per time step. © 1995.", "date": "1995-09-02T00:00:00Z", "citationCount": 8425, "authors": [ { "name": "Berendsen H.J.C." }, { "name": "van der Spoel D." }, { "name": "van Drunen R." } ], "journal": "Computer Physics Communications" } }, { "doi": "10.1002/jcc.24030", "pmid": "26238484", "pmcid": "PMC5042102", "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "Best bang for your buck: GPU nodes for GROMACS biomolecular simulations", "abstract": "The molecular dynamics simulation package GROMACS runs efficiently on a wide variety of hardware from commodity workstations to high performance computing clusters. Hardware features are well-exploited with a combination of single instruction multiple data, multithreading, and message passing interface (MPI)-based single program multiple data/multiple program multiple data parallelism while graphics processing units (GPUs) can be used as accelerators to compute interactions off-loaded from the CPU. Here, we evaluate which hardware produces trajectories with GROMACS 4.6 or 5.0 in the most economical way. We have assembled and benchmarked compute nodes with various CPU/GPU combinations to identify optimal compositions in terms of raw trajectory production rate, performance-to-price ratio, energy efficiency, and several other criteria. Although hardware prices are naturally subject to trends and fluctuations, general tendencies are clearly visible. Adding any type of GPU significantly boosts a node's simulation performance. For inexpensive consumer-class GPUs this improvement equally reflects in the performance-to-price ratio. Although memory issues in consumer-class GPUs could pass unnoticed as these cards do not support error checking and correction memory, unreliable GPUs can be sorted out with memory checking tools. Apart from the obvious determinants for cost-efficiency like hardware expenses and raw performance, the energy consumption of a node is a major cost factor. Over the typical hardware lifetime until replacement of a few years, the costs for electrical power and cooling can become larger than the costs of the hardware itself. Taking that into account, nodes with a well-balanced ratio of CPU and consumer-class GPU resources produce the maximum amount of GROMACS trajectory over their lifetime.", "date": "2015-10-01T00:00:00Z", "citationCount": 198, "authors": [ { "name": "Kutzner C." }, { "name": "Pall S." }, { "name": "Fechner M." }, { "name": "Esztermann A." }, { "name": "De Groot B.L." }, { "name": "Grubmuller H." } ], "journal": "Journal of Computational Chemistry" } }, { "doi": "10.1002/jcc.26011", "pmid": "31260119", "pmcid": null, "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "More bang for your buck: Improved use of GPU nodes for GROMACS 2018", "abstract": "We identify hardware that is optimal to produce molecular dynamics (MD) trajectories on Linux compute clusters with the GROMACS 2018 simulation package. Therefore, we benchmark the GROMACS performance on a diverse set of compute nodes and relate it to the costs of the nodes, which may include their lifetime costs for energy and cooling. In agreement with our earlier investigation using GROMACS 4.6 on hardware of 2014, the performance to price ratio of consumer GPU nodes is considerably higher than that of CPU nodes. However, with GROMACS 2018, the optimal CPU to GPU processing power balance has shifted even more toward the GPU. Hence, nodes optimized for GROMACS 2018 and later versions enable a significantly higher performance to price ratio than nodes optimized for older GROMACS versions. Moreover, the shift toward GPU processing allows to cheaply upgrade old nodes with recent GPUs, yielding essentially the same performance as comparable brand-new hardware. © 2019 Wiley Periodicals, Inc.", "date": "2019-10-15T00:00:00Z", "citationCount": 288, "authors": [ { "name": "Kutzner C." }, { "name": "Pall S." }, { "name": "Fechner M." }, { "name": "Esztermann A." }, { "name": "de Groot B.L." }, { "name": "Grubmuller H." } ], "journal": "Journal of Computational Chemistry" } } ], "credit": [ { "name": "GROMACS support", "email": null, "url": "http://www.gromacs.org/support/mailing_lists", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "jdianes", "additionDate": "2016-10-03T14:08:36Z", "lastUpdate": "2026-03-30T09:22:03.645037Z", "editPermission": { "type": "group", "authors": [ "adam.hospital@irbbarcelona.org", "gelpi@ub.edu", "sergitobara", "n.m.palmblad@lumc.nl" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "quac", "description": "QuaC is a snakemake-based pipeline that runs several QC tools for WGS/WES samples and then summarizes their results using pre-defined, configurable QC thresholds.", "homepage": "https://github.com/uab-cgds-worthey/quac", "biotoolsID": "quac", "biotoolsCURIE": "biotools:quac", "version": [ "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3218", "term": "Sequencing quality control" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [ "Sequencing" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/uab-cgds-worthey/quac", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/uab-cgds-worthey/quac/releases/tag/2.0", "type": "Source code", "note": null, "version": "2.0" } ], "documentation": [ { "url": "https://quac.readthedocs.io/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.21105/joss.05313", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Manavalan Gajapathy", "email": null, "url": "https://github.com/ManavalanG", "orcidid": "https://orcid.org/0000-0002-8606-0113", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "sdhutchins", "additionDate": "2026-03-26T02:15:51.819440Z", "lastUpdate": "2026-03-28T20:53:47.092010Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Rosalution", "description": "Rosalution assists researchers study genetic variation 🧬 in patients 🧑🏾🤝🧑🏼 by helping select candidate animal models 🐀🐁🐠🪱 to replicate the variation to further research to derive, diagnose, and provide therapies for ultra-rare diseases. 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A number of methods for comparing assemblers have been developed, but none is yet a recognized benchmark. Further, most existing methods for comparing assemblies are only applicable to new assemblies of finished genomes; the problem of evaluating assemblies of previously unsequenced species has not been adequately considered. Here, we present QUAST - a quality assessment tool for evaluating and comparing genome assemblies. This tool improves on leading assembly comparison software with new ideas and quality metrics. QUAST can evaluate assemblies both with a reference genome, as well as without a reference. QUAST produces many reports, summary tables and plots to help scientists in their research and in their publications. In this study, we used QUAST to compare several genome assemblers on three datasets. QUAST tables and plots for all of them are available in the Supplementary Material, and interactive versions of these reports are on the QUAST website. © 2013 The Author.", "date": "2013-04-15T00:00:00Z", "citationCount": 6872, "authors": [ { "name": "Gurevich A." }, { "name": "Saveliev V." }, { "name": "Vyahhi N." }, { "name": "Tesler G." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "QUAST Support", "email": "quast.support@cab.spbu.ru", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "seqwiki_import", "additionDate": "2017-01-13T13:16:01Z", "lastUpdate": "2026-03-13T09:39:06.494933Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-CZ", "Keiler_Collier", "rathor2611" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "EUCAIM Wizard Tool", "description": "The EUCAIM Wizard Tool performs an analysis of data re-identification risks of imaging and clinical data that follow the EUCAIM CDM. 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"webnma", "biotoolsCURIE": "biotools:webnma", "version": [ "3.5" ], "otherID": [], "relation": [ { "biotoolsID": "numpy", "type": "uses" }, { "biotoolsID": "biopython", "type": "uses" }, { "biotoolsID": "matplotlib", "type": "uses" }, { "biotoolsID": "mustang", "type": "uses" }, { "biotoolsID": "dssp", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0570", "term": "Structure visualisation" }, { "uri": "http://edamontology.org/operation_0244", "term": "Protein flexibility and motion analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_1354", "term": "Sequence profile" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": "Constructs elastic network model from alpha carbon coordinates of the protein, and computes properties to describe large scale conformations. Computes normal modes, fluctuation profiles, inter-residue correlations, conformational overlap analysis and vector field representations. Structural amino acid profiles, and normal mode characteristics describing protein motion, visualized in plots and decorated structure visualizations. White space delimited tabular data for normal modes and the provided plots", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2487", "term": "Protein structure comparison" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0886", "term": "Structure alignment" }, "format": [ { "uri": "http://edamontology.org/format_2200", "term": "FASTA-like (text)" } ] }, { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_0889", "term": "Structural profile" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": "Performs comparative analysis of the normal modes of protein structures. Computes the Bhattacharyya Coefficient (BC) and the Root Mean Squared Inner Product (RMSIP) of aligned parts of the proteins. Alignment of sets of proteins to be compared. Multiple protein structures Heatmaps, dendrograms and structural amino acid profiles for visual comparison of structural similarity. White space delimited tabular data for the provided plots", "cmd": null } ], "toolType": [ "Web API", "Suite" ], "topic": [ { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" }, { "uri": "http://edamontology.org/topic_0736", "term": "Protein folds and structural domains" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [ "BiB tools", "CBU tools", "UiB tools", "ELIXIR-NO", "ELIXIR-Norway" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Norway" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [ { "url": "https://github.com/reuter-group/webnma3", "type": [ "Repository", "Issue tracker" ], "note": null }, { "url": "https://elixir.no/helpdesk", "type": [ "Helpdesk" ], "note": "Helpdesk and support for ELIXIR Norway services." } ], "download": [], "documentation": [ { "url": "http://apps.cbu.uib.no/webnma3/howto/single", "type": [ "Quick start guide" ], "note": null }, { "url": "http://apps.cbu.uib.no/webnma3/qanda", "type": [ "FAQ" ], "note": null }, { "url": "http://apps.cbu.uib.no/webnma3/about", "type": [ "General", "Citation instructions" ], "note": null } ], "publication": [ { "doi": "10.1186/s12859-014-0427-6", "pmid": "25547242", "pmcid": "PMC4339738", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "WEBnmat v2.0: Web server and services for comparing protein flexibility", "abstract": "Background: Normal mode analysis (NMA) using elastic network models is a reliable and cost-effective computational method to characterise protein flexibility and by extension, their dynamics. Further insight into the dynamics-function relationship can be gained by comparing protein motions between protein homologs and functional classifications. This can be achieved by comparing normal modes obtained from sets of evolutionary related proteins. Results: We have developed an automated tool for comparative NMA of a set of pre-aligned protein structures. The user can submit a sequence alignment in the FASTA format and the corresponding coordinate files in the Protein Data Bank (PDB) format. The computed normalised squared atomic fluctuations and atomic deformation energies of the submitted structures can be easily compared on graphs provided by the web user interface. The web server provides pairwise comparison of the dynamics of all proteins included in the submitted set using two measures: the Root Mean Squared Inner Product and the Bhattacharyya Coefficient. The Comparative Analysis has been implemented on our web server for NMA, WEBnmat, which also provides recently upgraded functionality for NMA of single protein structures. This includes new visualisations of protein motion, visualisation of inter-residue correlations and the analysis of conformational change using the. In addition, programmatic access to WEBnmat is now available through a SOAP-based web service. WEBnmat is available at. Conclusion: WEBnmat v2.0 is an online tool offering unique capability for comparative NMA on multiple protein structures. Along with a convenient web interface, powerful computing resources, and several methods for mode analyses, WEBnmat facilitates the assessment of protein flexibility within protein families and superfamilies. These analyses can give a good view of how the structures move and how the flexibility is conserved over the different structures.", "date": "2014-12-30T00:00:00Z", "citationCount": 87, "authors": [ { "name": "Tiwari S.P." }, { "name": "Fuglebakk E." }, { "name": "Hollup S.M." }, { "name": "Skjaerven L." }, { "name": "Cragnolini T." }, { "name": "Grindhaug S.H." }, { "name": "Tekle K.M." }, { "name": "Reuter N." } ], "journal": "BMC Bioinformatics" } }, { "doi": "10.1186/1471-2105-6-52", "pmid": "15762993", "pmcid": "PMC1274249", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "WEBnm@: A web application for normal mode analyses of proteins", "abstract": "Background: Normal mode analysis (NMA) has become the method of choice to investigate the slowest motions in macromolecular systems. NMA is especially useful for large biomolecular assemblies, such as transmembrane channels or virus capsids. NMA relies on the hypothesis that the vibrational normal modes having the lowest frequencies (also named soft modes) describe the largest movements in a protein and are the ones that are functionally relevant. Results: We developed a web-based server to perform normal modes calculations and different types of analyses. Starting from a structure file provided by the user in the PDB format, the server calculates the normal modes and subsequently offers the user a series of automated calculations; normalized squared atomic displacements, vector field representation and animation of the first six vibrational modes. Each analysis is performed independently from the others and results can be visualized using only a web browser. No additional plug-in or software is required. For users who would like to analyze the results with their favorite software, raw results can also be downloaded. The application is available on http://www.bioinfo.no/tools/normalmodes. We present here the underlying theory, the application architecture and an illustration of its features using a large transmembrane protein as an example. Conclusion: We built an efficient and modular web application for normal mode analysis of proteins. Non specialists can easily and rapidly evaluate the degree of flexibility of multi-domain protein assemblies and characterize the large amplitude movements of their domains. © 2005 Hollup et al; licensee BioMed Central Ltd.", "date": "2005-03-11T00:00:00Z", "citationCount": 105, "authors": [ { "name": "Hollup S.M." }, { "name": "Salensminde G." }, { "name": "Reuter N." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Nathalie Reuter", "email": "Nathalie.Reuter@uib.no", "url": "http://www.cbu.uib.no/reuter/", "orcidid": "https://orcid.org/0000-0002-3649-7675", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer" ], "note": null }, { "name": "Sandhya P Tiwari", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-0747-3826", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Kidane M Tekle", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Tristan Cragnolini", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Svenn H Grindhaug", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Lars Skjærven", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Gisle Salensminde", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Edvin Fuglebakk", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Siv M Hollup", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Department of Molecular Biology, University of Bergen, Norway", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Computational Biology Unit, Department of Informatics, University of Bergen, Norway", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "UiB", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "UiB", "additionDate": "2016-03-17T13:51:10Z", "lastUpdate": "2026-03-11T08:56:55.566213Z", "editPermission": { "type": "group", "authors": [ "eca008", "korbinib" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "BioMercator", "description": "BioMercator is a software that provides a complete set of algorithms and visualization tool covering all steps required to perform QTL meta-analysis, graphical representation of large datasets. User may import sequence and genome annotations datasets within the software in order to display functional annotation related to QTL and meta-QTL.", "homepage": "https://sourcesup.renater.fr/projects/biomercator", "biotoolsID": "BioMercator", "biotoolsCURIE": "biotools:BioMercator", "version": [ "4.2.3" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0282", "term": "Genetic mapping" }, { "uri": "http://edamontology.org/operation_2944", "term": "Physical mapping" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1860", "term": "QTL map" }, "format": [ { "uri": "http://edamontology.org/format_2332", "term": "XML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_1288", "term": "Genome map" }, "format": [ { "uri": "http://edamontology.org/format_1975", "term": "GFF3" } ] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_3055", "term": "Quantitative genetics" }, { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://sourcesup.renater.fr/frs/?group_id=2301", "type": "Binaries", "note": null, "version": "4.2.3" } ], "documentation": [], "publication": [ { "doi": "10.1093/bioinformatics/bth230", "pmid": "15059820", "pmcid": null, "type": [], "version": "3", "note": null, "metadata": { "title": "BioMercator: Integrating genetic maps and QTL towards discovery of candidate genes", "abstract": "Summary: Breeding programs face the challenge of integrating information from genomics and from quantitative trait loci (QTL) analysis in order to identify genomic sequences controlling the variation of important traits. Despite the development of integrative databases, building a consensus map of genes, QTL and other loci gathered from multiple maps remains a manual and tedious task. Nevertheless, this is a critical step to reveal co-locations between genes and QTL. Another important matter is to determine whether QTL linked to same traits or related ones is detected in independent experiments and located in the same region, and represents a single locus or not. Statistical tools such as meta-analysis can be used to answer this question. BioMercator has been developed to automate map compilation and QTL meta-analysis, and to visualize co-locations between genes and QTL through a graphical interface. © Oxford University Press 2004; all rights reserved.", "date": "2004-09-22T00:00:00Z", "citationCount": 382, "authors": [ { "name": "Arcade A." }, { "name": "Labourdette A." }, { "name": "Falque M." }, { "name": "Mangin B." }, { "name": "Chardon F." }, { "name": "Charcosset A." }, { "name": "Joets J." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "admin", "additionDate": "2019-09-27T09:58:46Z", "lastUpdate": "2026-03-11T08:56:54.859634Z", "editPermission": { "type": "group", "authors": [ "b.guerra01" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "SERtool", "description": "Detection of Sequence-Enriched Regions (SER) in Proteins and Nucleic Acids", "homepage": "https://github.com/rennmeng/SERtool", "biotoolsID": "sertool", "biotoolsCURIE": "biotools:sertool", "version": [ "1.0.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0291", "term": "Sequence clustering" } ], "input": [], "output": [], "note": "Independent scan for 20 amino acids", "cmd": "python SERtool.py A,C,D,E,F,G,H,I,K,L,M,N,P,Q,R,S,T,V,W,Y --input test.fasta --start 20 --point 18 20 30 50" }, { "operation": [ { "uri": "http://edamontology.org/operation_0291", "term": "Sequence clustering" } ], "input": [], "output": [], "note": "Same class D-E analysis", "cmd": "python SERtool.py D-E --input test.fasta --start 20 --point 18 20 30 50" }, { "operation": [ { "uri": "http://edamontology.org/operation_0291", "term": "Sequence clustering" } ], "input": [], "output": [], "note": "Wildcard: all X-S motifs (e.g., DS, RS)", "cmd": "python SERtool.py .S --input test.fasta --start 15 --point 5 10 10 30" } ], "toolType": [ "Bioinformatics portal", "Web service", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_0160", "term": "Sequence sites, features and motifs" } ], "operatingSystem": [ "Linux" ], "language": [ "Rust", "Python" ], "license": "MIT", "collectionID": [], "maturity": "Legacy", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/rennmeng/SERtool", "type": [ "Repository" ], "note": null }, { "url": "https://www.sertool.net/", "type": [ "Service" ], "note": null } ], "download": [ { "url": "https://www.sertool.net/resource", "type": "Downloads page", "note": null, "version": "1.0.1" } ], "documentation": [ { "url": "https://www.sertool.net/help", "type": [ "User manual" ], "note": null } ], "publication": [], "credit": [ { "name": "Meng Ren", "email": "rennmeng@smail.nju.edu.cn", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "rennmeng", "additionDate": "2025-09-25T00:18:49.762990Z", "lastUpdate": "2026-03-11T03:31:16.480486Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "RMSX and Flipbook", "description": "RMSX + Flipbook is a molecular dynamics analysis and visualization tool for generating residue-resolved structural motion summaries from simulation trajectories. 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Pangenomes may be represented as graphical structures, e.g. compacted colored de Bruijn graphs, which offer a low memory usage and facilitate reference-free sequence comparisons. While sequence-to-graph mapping to graphical pangenomes has been studied for some time, no local alignment search tool in the vein of BLAST has been proposed yet. Results: We present a new heuristic method to find maximum scoring local alignments of a DNA query sequence to a pangenome represented as a compacted colored de Bruijn graph. Our approach additionally allows a comparison of similarity among sequences within the pangenome. We show that local alignment scores follow an exponential-tail distribution similar to BLAST scores, and we discuss how to estimate its parameters to separate local alignments representing sequence homology from spurious findings. An implementation of our method is presented, and its performance and usability are shown. Our approach scales sublinearly in running time and memory usage with respect to the number of genomes under consideration. 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