TopoLink: evaluation of structural models using chemical crosslinking distance constraints

2019 ◽  
Vol 35 (17) ◽  
pp. 3169-3170 ◽  
Author(s):  
Allan J R Ferrari ◽  
Milan A Clasen ◽  
Louise Kurt ◽  
Paulo C Carvalho ◽  
Fabio C Gozzo ◽  
...  
Keyword(s):  
Source Code ◽  
Structural Models ◽  
Free Software ◽  
Supplementary Information ◽  
Minimum Length ◽  
Chemical Crosslinking ◽  
Graphical Interface ◽  
Protein Size ◽  
Model Consistency ◽  
User Friendly

Abstract Summary A software was developed to evaluate structural models using chemical crosslinking experiments. The user provides the types of linkers used and their reactivity, and the observed crosslinks and dead-ends. The software computes the minimum length of a physically inspired linker that connects the reactive atoms of interest, and reports the consistency of each distance with the experimental observation. Statistics on model consistency with the links are provided. Tools to evaluate the correlation of crosslinks in ensembles of models were developed. TopoLink was used to evaluate the potential crosslinks of all structures of the CATH database. The number of crosslinks expected as a function of protein size and linker length can be used as guide for experimental design. Availability and implementation TopoLink is available as free software at http://m3g.iqm.unicamp.br/topolink, and distributed as source code with a user-friendly graphical interface for Windows. A web server is also provided. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Temporal network alignment via GoT-WAVE

2019 ◽  
Vol 35 (18) ◽  
pp. 3527-3529 ◽  
Author(s):  
David Aparício ◽  
Pedro Ribeiro ◽  
Tijana Milenković ◽  
Fernando Silva
Keyword(s):  
User Interface ◽  
State Of The Art ◽  
Source Code ◽  
Network Alignment ◽  
Supplementary Information ◽  
Temporal Network ◽  
Temporal Networks ◽  
Supplementary Data ◽  
Node Similarity ◽  
User Friendly

Abstract Motivation Network alignment (NA) finds conserved regions between two networks. NA methods optimize node conservation (NC) and edge conservation. Dynamic graphlet degree vectors are a state-of-the-art dynamic NC measure, used within the fastest and most accurate NA method for temporal networks: DynaWAVE. Here, we use graphlet-orbit transitions (GoTs), a different graphlet-based measure of temporal node similarity, as a new dynamic NC measure within DynaWAVE, resulting in GoT-WAVE. Results On synthetic networks, GoT-WAVE improves DynaWAVE’s accuracy by 30% and speed by 64%. On real networks, when optimizing only dynamic NC, the methods are complementary. Furthermore, only GoT-WAVE supports directed edges. Hence, GoT-WAVE is a promising new temporal NA algorithm, which efficiently optimizes dynamic NC. We provide a user-friendly user interface and source code for GoT-WAVE. Availability and implementation http://www.dcc.fc.up.pt/got-wave/ Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals DamageProfiler: Fast damage pattern calculation for ancient DNA

2021 ◽  
Author(s):  
Judith Neukamm ◽  
Alexander Peltzer ◽  
Kay Nieselt
Keyword(s):  
Ancient Dna ◽  
Source Code ◽  
Supplementary Information ◽  
Command Line ◽  
Central Importance ◽  
Command Line Interface ◽  
Analysis Pipeline ◽  
File Formats ◽  
Programming Knowledge ◽  
User Friendly

Abstract Motivation In ancient DNA research, the authentication of ancient samples based on specific features remains a crucial step in data analysis. Because of this central importance, researchers lacking deeper programming knowledge should be able to run a basic damage authentication analysis. Such software should be user-friendly and easy to integrate into an analysis pipeline. Results DamageProfiler is a Java based, stand-alone software to determine damage patterns in ancient DNA. The results are provided in various file formats and plots for further processing. DamageProfiler has an intuitive graphical as well as command line interface that allows the tool to be easily embedded into an analysis pipeline. Availability All of the source code is freely available on GitHub (https://github.com/Integrative-Transcriptomics/DamageProfiler). Supplementary information Supplementary data are available at Bioinformatics online.

CellTracker (not only) for dummies

2015 ◽  
Vol 32 (6) ◽  
pp. 955-957 ◽  
Author(s):  
Filippo Piccinini ◽  
Alexa Kiss ◽  
Peter Horvath
Keyword(s):  
Graphical User Interface ◽  
Open Source Software ◽  
Phase Contrast ◽  
Cell Tracking ◽  
Source Code ◽  
Software Tool ◽  
Time Lapse ◽  
Supplementary Information ◽  
Differential Interference Contrast ◽  
User Friendly

Abstract Motivation: Time-lapse experiments play a key role in studying the dynamic behavior of cells. Single-cell tracking is one of the fundamental tools for such analyses. The vast majority of the recently introduced cell tracking methods are limited to fluorescently labeled cells. An equally important limitation is that most software cannot be effectively used by biologists without reasonable expertise in image processing. Here we present CellTracker, a user-friendly open-source software tool for tracking cells imaged with various imaging modalities, including fluorescent, phase contrast and differential interference contrast (DIC) techniques. Availability and implementation: CellTracker is written in MATLAB (The MathWorks, Inc., USA). It works with Windows, Macintosh and UNIX-based systems. Source code and graphical user interface (GUI) are freely available at: http://celltracker.website/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

scholarly journals PyXlinkViewer: a flexible tool for visualisation of protein chemical crosslinking data within the PyMOL molecular graphics system

2020 ◽  
Author(s):  
Bob Schiffrin ◽  
Sheena. E. Radford ◽  
David. J. Brockwell ◽  
Antonio N. Calabrese
Keyword(s):  
High Resolution ◽  
Protein Structures ◽  
Structural Models ◽  
Structural Data ◽  
Chemical Crosslinking ◽  
Molecular Graphics ◽  
Flexible Tool ◽  
Dead End ◽  
Spacer Arm ◽  
User Friendly

AbstractChemical crosslinking-mass spectrometry (XL-MS) is a valuable technique for gaining insights into protein structure and the organization of macromolecular complexes. XL-MS data yields inter-residue restraints that can be compared with high-resolution structural data. Distances greater than the crosslinker spacer-arm can reveal lowly-populated “excited” states of proteins/protein assemblies, or crosslinks can be used as restraints to generate structural models in the absence of structural data. Despite increasing uptake of XL-MS, there are few tools to enable rapid and facile mapping of XL-MS data onto high-resolution structures or structural models. PyXlinkViewer is a user-friendly plugin for PyMOL v2 that maps intra-protein, inter-protein and dead-end crosslinks onto protein structures/models and automates the calculation of inter-residue distances for the detected crosslinks. This enables rapid visualisation of XL-MS data, assessment of whether a set of detected crosslinks is congruent with structural data, and easy production of high-quality images for publication.

scholarly journals MOSGA: Modular Open-Source Genome Annotator

2020 ◽  
Author(s):  
Roman Martin ◽  
Thomas Hackl ◽  
Georges Hattab ◽  
Matthias G Fischer ◽  
Dominik Heider
Keyword(s):  
Open Source ◽  
Source Code ◽  
Supplementary Information ◽  
Web Interface ◽  
Fully Integrated ◽  
Sequencing Technologies ◽  
A Genome ◽  
Wide Range ◽  
User Friendly ◽  
Eukaryotic Genomes

Abstract Motivation The generation of high-quality assemblies, even for large eukaryotic genomes, has become a routine task for many biologists thanks to recent advances in sequencing technologies. However, the annotation of these assemblies—a crucial step toward unlocking the biology of the organism of interest—has remained a complex challenge that often requires advanced bioinformatics expertise. Results Here, we present MOSGA (Modular Open-Source Genome Annotator), a genome annotation framework for eukaryotic genomes with a user-friendly web-interface that generates and integrates annotations from various tools. The aggregated results can be analyzed with a fully integrated genome browser and are provided in a format ready for submission to NCBI. MOSGA is built on a portable, customizable and easily extendible Snakemake backend, and thus, can be tailored to a wide range of users and projects. Availability and implementation We provide MOSGA as a web service at https://mosga.mathematik.uni-marburg.de and as a docker container at registry.gitlab.com/mosga/mosga: latest. Source code can be found at https://gitlab.com/mosga/mosga Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Gcluster: a simple-to-use tool for visualizing and comparing genome contexts for numerous genomes

2020 ◽  
Vol 36 (12) ◽  
pp. 3871-3873 ◽  
Author(s):  
Xiangyang Li ◽  
Fang Chen ◽  
Yunpeng Chen
Keyword(s):  
Source Code ◽  
Gene Clusters ◽  
Genomic Region ◽  
Supplementary Information ◽  
Homologous Gene ◽  
High Quality ◽  
Large Numbers ◽  
Linear Maps ◽  
User Friendly

Abstract Motivation Comparing the organization of gene, gene clusters and their flanking genomic contexts is of critical importance to the determination of gene function and evolutionary basis of microbial traits. Currently, user-friendly and flexible tools enabling to visualize and compare genomic contexts for numerous genomes are still missing. Results We here present Gcluster, a stand-alone Perl tool that allows researchers to customize and create high-quality linear maps of the genomic region around the genes of interest across large numbers of completed and draft genomes. Importantly, Gcluster integrates homologous gene analysis, in the form of a built-in orthoMCL, and mapping genomes onto a given phylogeny to provide superior comparison of gene contexts. Availability and implementation Gcluster is written in Perl and released under GPLv3. The source code is freely available at https://github.com/Xiangyang1984/Gcluster and http://www.microbialgenomic.com/Gcluster_tool.html. Gcluster can also be installed through conda: ‘conda install -c bioconda gcluster’. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals mixtureS: a novel tool for bacterial strain genome reconstruction from reads

2020 ◽  
Author(s):  
Xin Li ◽  
Haiyan Hu ◽  
Xiaoman Li
Keyword(s):  
Environmental Samples ◽  
De Novo ◽  
Source Code ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Bacterial Strains ◽  
Metagenomic Sample ◽  
Almost All ◽  
User Friendly ◽  
Strain Genome

Abstract Motivation It is essential to study bacterial strains in environmental samples. Existing methods and tools often depend on known strains or known variations, cannot work on individual samples, not reliable, or not easy to use, etc. It is thus important to develop more user-friendly tools that can identify bacterial strains more accurately. Results We developed a new tool called mixtureS that can de novo identify bacterial strains from shotgun reads of a clonal or metagenomic sample, without prior knowledge about the strains and their variations. Tested on 243 simulated datasets and 195 experimental datasets, mixtureS reliably identified the strains, their numbers and their abundance. Compared with three tools, mixtureS showed better performance in almost all simulated datasets and the vast majority of experimental datasets. Availability and implementation The source code and tool mixtureS is available at http://www.cs.ucf.edu/˜xiaoman/mixtureS/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals The Encyclopedia of Proteome Dynamics: the KinoViewer

2018 ◽  
Vol 35 (8) ◽  
pp. 1441-1442 ◽  
Author(s):  
Alejandro Brenes ◽  
Angus I Lamond
Keyword(s):  
Open Access ◽  
Supplementary Information ◽  
Analysis Tool ◽  
Graphical Display ◽  
Visualization Tool ◽  
Dynamic Visualization ◽  
Graphical Interface ◽  
Mouse Cells ◽  
Interactive Data ◽  
User Friendly

Abstract Summary The Encyclopedia of Proteome Dynamics (EPD) ‘KinoViewer’ is an interactive data visualization tool designed for analysis and exploration of both protein and transcript data, showing expression of kinase genes in either human or mouse cells and tissues. The KinoViewer provides a comprehensive, updated graphical display of all human/mouse kinases and an open access analysis tool for the community with a user-friendly graphical interface. Availability and implementation The KinoViewer is based on a manually drawn SVG, which is utilized with D3.js to create a dynamic visualization. It can be accessed at: https://peptracker.com/epd/analytics/. The KinoViewer is currently only accessible through the EPD, it is open access and can be used either to view internal datasets, or used to upload and visualize external user datasets. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals The CroCo cross-link converter: a user-centred tool to convert results from cross-linking mass spectrometry experiments

2019 ◽  
Author(s):  
Julian Bender ◽  
Carla Schmidt
Keyword(s):  
Mass Spectrometry ◽  
Source Code ◽  
Supplementary Information ◽  
Cross Linking ◽  
Cross Link ◽  
Research Areas ◽  
Visualization Tools ◽  
User Friendly ◽  
General Public License ◽  
Selection Of

Abstract Motivation A variety of search engines exists for the identification of peptide spectrum matches after cross-linking mass spectrometry experiments. The resulting diversity in output formats complicates data validation and visualization as well as exchange with collaborators, particularly from other research areas. Results Here, we present CroCo, a user-friendly standalone executable to convert cross-linking results to a comprehensive spreadsheet format. Using this format, CroCo can be employed to generate input files for a selection of the commonly utilized validation and visualization tools. Availability and implementation The source-code is freely available under a GNU general public license at https://github.com/cschmidtlab/croco. The standalone executable is available and documented at https://cschmidtlab.github.io/CroCo. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals VCF/Plotein: visualization and prioritization of genomic variants from human exome sequencing projects

2019 ◽  
Vol 35 (22) ◽  
pp. 4803-4805 ◽  
Author(s):  
Raul Ossio ◽  
O Isaac Garcia-Salinas ◽  
Diego Said Anaya-Mancilla ◽  
Jair S Garcia-Sotelo ◽  
Luis A Aguilar ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Web Application ◽  
Source Code ◽  
Supplementary Information ◽  
Sequencing Data ◽  
Genomic Variants ◽  
Exome Sequencing Data ◽  
Variant Filtering ◽  
Variant Information ◽  
User Friendly

Abstract Motivation Identifying disease-causing variants from exome sequencing projects remains a challenging task that often requires bioinformatics expertise. Here we describe a user-friendly graphical application that allows medical professionals and bench biologists to prioritize and visualize genetic variants from human exome sequencing data. Results We have implemented VCF/Plotein, a graphical, fully interactive web application able to display exome sequencing data in VCF format. Gene and variant information is extracted from Ensembl. Cross-referencing with external databases and application-based gene and variant filtering have also been implemented. All data processing is done locally by the user’s CPU to ensure the security of patient data. Availability and implementation Freely available on the web at https://vcfplotein.liigh.unam.mx. Website implemented in JavaScript using the Vue.js framework, with all major browsers supported. Source code freely available for download at https://github.com/raulossio/VCF-plotein. Supplementary information Supplementary data are available at Bioinformatics online.

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