scholarly journals SEABED: Small molEcule activity scanner weB servicE baseD

2014 ◽  
Vol 31 (5) ◽  
pp. 773-775 ◽  
Author(s):  
Carlos Fenollosa ◽  
Marcel Otón ◽  
Pau Andrio ◽  
Jorge Cortés ◽  
Modesto Orozco ◽  
...  
Keyword(s):  
Web Service ◽  
Web Server ◽  
Software As A Service ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Ensemble Docking ◽  
Web Tools ◽  
Protein Mutants ◽  
User Friendly ◽  
Hybrid Docking

Abstract Motivation: The SEABED web server integrates a variety of docking and QSAR techniques in a user-friendly environment. SEABED goes beyond the basic docking and QSAR web tools and implements extended functionalities like receptor preparation, library editing, flexible ensemble docking, hybrid docking/QSAR experiments or virtual screening on protein mutants. SEABED is not a monolithic workflow tool but Software as a Service platform. Availability and implementation: SEABED is a free web server available athttp://www.bsc.es/SEABED. No registration is required. Contact: [email protected] Supplementary information: Supplementary data are available atBioinformatics online.

scholarly journals COVID-19 Docking Server: a meta server for docking small molecules, peptides and antibodies against potential targets of COVID-19

2020 ◽  
Vol 36 (20) ◽  
pp. 5109-5111 ◽  
Author(s):  
Ren Kong ◽  
Guangbo Yang ◽  
Rui Xue ◽  
Ming Liu ◽  
Feng Wang ◽  
...  
Keyword(s):  
Life Cycle ◽  
Drug Discovery ◽  
Small Molecules ◽  
Web Server ◽  
Supplementary Information ◽  
Binding Modes ◽  
Supplementary Data ◽  
Virus Life Cycle ◽  
Ligand Interactions ◽  
New Type

Abstract Motivation The coronavirus disease 2019 (COVID-19) caused by a new type of coronavirus has been emerging from China and led to thousands of death globally since December 2019. Despite many groups have engaged in studying the newly emerged virus and searching for the treatment of COVID-19, the understanding of the COVID-19 target–ligand interactions represents a key challenge. Herein, we introduce COVID-19 Docking Server, a web server that predicts the binding modes between COVID-19 targets and the ligands including small molecules, peptides and antibodies. Results Structures of proteins involved in the virus life cycle were collected or constructed based on the homologs of coronavirus, and prepared ready for docking. The meta-platform provides a free and interactive tool for the prediction of COVID-19 target–ligand interactions and following drug discovery for COVID-19. Availability and implementation http://ncov.schanglab.org.cn. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals YeastSpotter: accurate and parameter-free web segmentation for microscopy images of yeast cells

2019 ◽  
Vol 35 (21) ◽  
pp. 4525-4527 ◽  
Author(s):  
Alex X Lu ◽  
Taraneh Zarin ◽  
Ian S Hsu ◽  
Alan M Moses
Keyword(s):  
Image Analysis ◽  
Web Application ◽  
Single Cells ◽  
Yeast Cells ◽  
Supplementary Information ◽  
Supplementary Data ◽  
User Friendly ◽  
Microscopy Images

Abstract Summary We introduce YeastSpotter, a web application for the segmentation of yeast microscopy images into single cells. YeastSpotter is user-friendly and generalizable, reducing the computational expertise required for this critical preprocessing step in many image analysis pipelines. Availability and implementation YeastSpotter is available at http://yeastspotter.csb.utoronto.ca/. Code is available at https://github.com/alexxijielu/yeast_segmentation. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals INDRA-IPM: interactive pathway modeling using natural language with automated assembly

2019 ◽  
Vol 35 (21) ◽  
pp. 4501-4503 ◽  
Author(s):  
Petar V Todorov ◽  
Benjamin M Gyori ◽  
John A Bachman ◽  
Peter K Sorger
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Web Service ◽  
Language Processing ◽  
Source Code ◽  
Supplementary Information ◽  
Expression Data ◽  
Supplementary Data ◽  
Automated Assembly ◽  
Web Based

Abstract Summary INDRA-IPM (Interactive Pathway Map) is a web-based pathway map modeling tool that combines natural language processing with automated model assembly and visualization. INDRA-IPM contextualizes models with expression data and exports them to standard formats. Availability and implementation INDRA-IPM is available at: http://pathwaymap.indra.bio. Source code is available at http://github.com/sorgerlab/indra_pathway_map. The underlying web service API is available at http://api.indra.bio:8000. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals MitoTrack, a user-friendly semi-automatic software for lineage tracking in living embryos

2019 ◽  
Author(s):  
A Trullo ◽  
J Dufourt ◽  
M Lagha
Keyword(s):  
Graphical User Interface ◽  
Transcriptional Activation ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Automatic Image Analysis ◽  
Lineage Tree ◽  
Automatic Software ◽  
Integrated Software ◽  
Lineage Tracking ◽  
User Friendly

Abstract Motivation During development, progenitor cells undergo multiple rounds of cellular divisions during which transcriptional programs must be faithfully propagated. Investigating the timing of transcriptional activation, which is a highly stochastic phenomenon, requires the analysis of large amounts of data. In order to perform automatic image analysis of transcriptional activation, we developed a software that segments and tracks both small and large objects, leading the user from raw data up to the results in their final form. Results MitoTrack is a user-friendly open-access integrated software that performs the specific dual task of reporting the precise timing of transcriptional activation while keeping lineage tree history for each nucleus of a living developing embryo. The software works automatically but provides the possibility to easily supervise, correct and validate each step. Availability and implementation MitoTrack is an open source Python software, embedded within a graphical user interface (download here). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals MetumpX—a metabolomics support package for untargeted mass spectrometry

2019 ◽  
Vol 36 (5) ◽  
pp. 1647-1648 ◽  
Author(s):  
Bilal Wajid ◽  
Hasan Iqbal ◽  
Momina Jamil ◽  
Hafsa Rafique ◽  
Faria Anwar
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Small Molecules ◽  
Software Package ◽  
Life Sciences ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Software Packages ◽  
Develop Software ◽  
User Friendly

Abstract Motivation Metabolomics is a data analysis and interpretation field aiming to study functions of small molecules within the organism. Consequently Metabolomics requires researchers in life sciences to be comfortable in downloading, installing and scripting of software that are mostly not user friendly and lack basic GUIs. As the researchers struggle with these skills, there is a dire need to develop software packages that can automatically install software pipelines truly speeding up the learning curve to build software workstations. Therefore, this paper aims to provide MetumpX, a software package that eases in the installation of 103 software by automatically resolving their individual dependencies and also allowing the users to choose which software works best for them. Results MetumpX is a Ubuntu-based software package that facilitate easy download and installation of 103 tools spread across the standard metabolomics pipeline. As far as the authors know MetumpX is the only solution of its kind where the focus lies on automating development of software workstations. Availability and implementation https://github.com/hasaniqbal777/MetumpX-bin. 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 GladiaTOX: GLobal Assessment of Dose-IndicAtor in TOXicology

2019 ◽  
Vol 35 (20) ◽  
pp. 4190-4192 ◽  
Author(s):  
Vincenzo Belcastro ◽  
Stephane Cano ◽  
Diego Marescotti ◽  
Stefano Acali ◽  
Carine Poussin ◽  
...  
Keyword(s):  
Quality Control ◽  
Data Processing ◽  
Web Service ◽  
Biomedical Research ◽  
Global Assessment ◽  
R Package ◽  
Supplementary Information ◽  
High Content Screening ◽  
Supplementary Data ◽  
Severity Scores

Abstract Summary GladiaTOX R package is an open-source, flexible solution to high-content screening data processing and reporting in biomedical research. GladiaTOX takes advantage of the ‘tcpl’ core functionalities and provides a number of extensions: it provides a web-service solution to fetch raw data; it computes severity scores and exports ToxPi formatted files; furthermore it contains a suite of functionalities to generate PDF reports for quality control and data processing. Availability and implementation GladiaTOX R package (bioconductor). Also available via: git clone https://github.com/philipmorrisintl/GladiaTOX.git. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals JSpeciesWS: a web server for prokaryotic species circumscription based on pairwise genome comparison

2015 ◽  
Vol 32 (6) ◽  
pp. 929-931 ◽  
Author(s):  
Michael Richter ◽  
Ramon Rosselló-Móra ◽  
Frank Oliver Glöckner ◽  
Jörg Peplies
Keyword(s):  
Draft Genome ◽  
Web Server ◽  
Supplementary Information ◽  
Genome Comparison ◽  
Reference Database ◽  
Online Service ◽  
Genome Sequences ◽  
Species Circumscription ◽  
Correlation Search ◽  
User Friendly

Abstract Summary: JSpecies Web Server (JSpeciesWS) is a user-friendly online service for in silico calculating the extent of identity between two genomes, a parameter routinely used in the process of polyphasic microbial species circumscription. The service measures the average nucleotide identity (ANI) based on BLAST+ (ANIb) and MUMmer (ANIm), as well as correlation indexes of tetra-nucleotide signatures (Tetra). In addition, it provides a Tetra Correlation Search function, which allows to rapidly compare selected genomes against a continuously updated reference database with currently about 32 000 published whole and draft genome sequences. For comparison, own genomes can be uploaded and references can be selected from the JSpeciesWS reference database. The service indicates whether two genomes share genomic identities above or below the species embracing thresholds, and serves as a fast way to allocate unknown genomes in the frame of the hitherto sequenced species. Availability and implementation: JSpeciesWS is available at http://jspecies.ribohost.com/jspeciesws. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: [email protected]

scholarly journals DINC-COVID: A webserver for ensemble docking with flexible SARS-CoV-2 proteins

2021 ◽  
Author(s):  
Sarah Hall-Swan ◽  
Dinler A. Antunes ◽  
Didier Devaurs ◽  
Mauricio M. Rigo ◽  
Lydia E. Kavraki ◽  
...  
Keyword(s):  
Supplementary Information ◽  
Scoring Functions ◽  
Binding Modes ◽  
Computational Tool ◽  
Receptor Flexibility ◽  
Ensemble Docking ◽  
Main Protease ◽  
Docking Tool ◽  
Supplementary Material ◽  
User Friendly

AbstractMotivationRecent efforts to computationally identify inhibitors for SARS-CoV-2 proteins have largely ignored the issue of receptor flexibility. We have implemented a computational tool for ensemble docking with the SARS-CoV-2 proteins, including the main protease (Mpro), papain-like protease (PLpro) and RNA-dependent RNA polymerase (RdRp).ResultsEnsembles of other SARS-CoV-2 proteins are being prepared and made available through a user-friendly docking interface. Plausible binding modes between conformations of a selected ensemble and an uploaded ligand are generated by DINC, our parallelized meta-docking tool. Binding modes are scored with three scoring functions, and account for the flexibility of both the ligand and receptor. Additional details on our methods are provided in the supplementary material.Availabilitydinc-covid.kavrakilab.orgSupplementary informationDetails on methods for ensemble generation and docking are provided as supplementary data [email protected], [email protected]

scholarly journals dittoSeq: universal user-friendly single-cell and bulk RNA sequencing visualization toolkit

2020 ◽  
Author(s):  
Daniel G Bunis ◽  
Jared Andrews ◽  
Gabriela K Fragiadakis ◽  
Trevor D Burt ◽  
Marina Sirota
Keyword(s):  
Single Cell ◽  
R Package ◽  
Color Blindness ◽  
Ease Of Use ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Rnaseq Data ◽  
Visualization Toolkit ◽  
User Friendly ◽  
Publication Quality

Abstract Summary A visualization suite for major forms of bulk and single-cell RNAseq data in R. dittoSeq is color blindness-friendly by default, robustly documented to power ease-of-use and allows highly customizable generation of both daily-use and publication-quality figures. Availability and implementation dittoSeq is an R package available through Bioconductor via an open source MIT license. Supplementary information Supplementary data are available at Bioinformatics online.

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