scholarly journals INTERSPIA: a web application for exploring the dynamics of protein-protein interactions among multiple species

2018 ◽  
Vol 46 (W1) ◽  
pp. W89-W94 ◽  
Author(s):  
Daehong Kwon ◽  
Daehwan Lee ◽  
Juyeon Kim ◽  
Jongin Lee ◽  
Mikang Sim ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Web Application ◽  
Protein Protein Interactions ◽  
Multiple Species

NetSets.js: a JavaScript framework for compositional assessment and comparison of biological networks through Venn-integrated network diagrams

2020 ◽  
Author(s):  
Sunil Nagpal ◽  
Bhusan K Kuntal ◽  
Sharmila S Mande
Keyword(s):  
Protein Interactions ◽  
Biological Networks ◽  
Web Application ◽  
Gene Interaction ◽  
Supplementary Information ◽  
Venn Diagram ◽  
Protein Protein Interactions ◽  
Integrated Network ◽  
Network Diagram ◽  
Network Diagrams

Abstract Motivation Venn diagrams are frequently used to compare composition of datasets (e.g. datasets containing list of proteins and genes). Network diagram constructed using such datasets are usually generated using ‘list of edges’, popularly known as edge-lists. An edge-list and the corresponding generated network are, however, composed of two elements, namely, edges (e.g. protein–protein interactions) and nodes (e.g. proteins). Researchers often use individual lists of edges and nodes to compare composition of biological networks using existing Venn diagram tools. However, specialized analysis workflows are required for comparison of nodes as well as edges. Apart from this, different tools or graph libraries are needed for visualizing any specific edges of interest (e.g. protein–protein interactions which are present across all networks or are shared between subset of networks or are exclusively present in a selected network). Further, these results are required to be exported in the form of publication worthy network diagram(s), particularly for small networks. Results We introduce a (server independent) JavaScript framework (called NetSets.js) that integrates popular Venn and network diagrams in a single application. A free to use intuitive web application (utilizing NetSets.js), specifically designed to perform both compositional comparisons (e.g. for identifying common/exclusive edges or nodes) and interactive user defined visualizations of network (for the identified common/exclusive interactions across multiple networks) using simple edge-lists is also presented. The tool also enables connection to Cytoscape desktop application using the Netsets-Cyapp. We demonstrate the utility of our tool using real world biological networks (microbiome, gene interaction, multiplex and protein–protein interaction networks). Availabilityand implementation http://web.rniapps.net/netsets (freely available for academic use). Supplementary information Supplementary data are available at Bioinformatics online.

Using INTERSPIA to Explore the Dynamics of Protein‐Protein Interactions Among Multiple Species

2019 ◽  
Vol 68 (1) ◽  
Author(s):  
Daehong Kwon ◽  
Daehwan Lee ◽  
Juyeon Kim ◽  
Jongin Lee ◽  
Mikang Sim ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Protein Protein Interactions ◽  
Multiple Species

scholarly journals PPISearch: a web server for searching homologous protein–protein interactions across multiple species

2009 ◽  
Vol 37 (suppl_2) ◽  
pp. W369-W375 ◽  
Author(s):  
Chun-Chen Chen ◽  
Chun-Yu Lin ◽  
Yu-Shu Lo ◽  
Jinn-Moon Yang
Keyword(s):  
Protein Interactions ◽  
Web Server ◽  
Protein Protein Interactions ◽  
Homologous Protein ◽  
Multiple Species

scholarly journals ProfPPIdb: pairs of physical protein-protein interactions predicted for entire proteomes

2018 ◽  
Author(s):  
Linh Tran ◽  
Tobias Hamp ◽  
Burkhard Rost
Keyword(s):  
Experimental Data ◽  
Protein Interactions ◽  
Web Application ◽  
Domain Knowledge ◽  
Prediction Method ◽  
Model Organisms ◽  
Evolutionary Information ◽  
Support Vector ◽  
Protein Protein Interactions ◽  
Link Type

AbstractMotivationProtein-protein interactions (PPIs) play a key role in many cellular processes. Most annotations of PPIs mix experimental and computational data. The mix optimizes coverage, but obfuscates the annotation origin. Some resources excel at focusing on reliable experimental data. Here, we focused on new pairs of interacting proteins for several model organisms based solely on sequence-based prediction methods.ResultsWe extracted reliable experimental data about which proteins interact (binary) for eight diverse model organisms from public databases, namely from Escherichia coli, Schizosaccharomyces pombe, Plasmodium falciparum, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, Rattus norvegicus, Arabidopsis thaliana, and for the previously used Homo sapiens and Saccharomyces cerevisiae. Those data were the base to develop a PPI prediction method for each model organism. The method used evolutionary information through a profile-kernel Support Vector Machine (SVM). With the resulting eight models, we predicted all possible protein pairs in each organism and made the top predictions available through a web application. Almost all of the PPIs made available were predicted between proteins that have not been observed in any interaction, in particular for less well-studied organisms. Thus, our work complements existing resources and is particularly helpful for designing experiments because of its uniqueness. Experimental annotations and computational predictions are strongly influenced by the fact that some proteins have many partners and others few. To optimize machine learning, recent methods explicitly ignored such a network-structure and rely either on domain knowledge or sequence-only methods. Our approach is independent of domain-knowledge and leverages evolutionary information. The database interface representing our results is accessible from https://rostlab.org/services/ppipair/. The data can also be downloaded from https://figshare.com/collections/ProfPPI-DB/4141784.

scholarly journals BAlaS: fast, interactive and accessible computational alanine-scanning using BudeAlaScan

2020 ◽  
Vol 36 (9) ◽  
pp. 2917-2919 ◽  
Author(s):  
Christopher W Wood ◽  
Amaurys A Ibarra ◽  
Gail J Bartlett ◽  
Andrew J Wilson ◽  
Derek N Woolfson ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Protein Interactions ◽  
Interface Design ◽  
Web Application ◽  
Side Chain ◽  
Protein Interface ◽  
Protein Protein Interactions ◽  
Alanine Scanning Mutagenesis ◽  
Alanine Scanning ◽  
Computational Alanine Scanning

Abstract Motivation In experimental protein engineering, alanine-scanning mutagenesis involves the replacement of selected residues with alanine to determine the energetic contribution of each side chain to forming an interaction. For example, it is often used to study protein–protein interactions. However, such experiments can be time-consuming and costly, which has led to the development of programmes for performing computational alanine-scanning mutagenesis (CASM) to guide experiments. While programmes are available for this, there is a need for a real-time web application that is accessible to non-expert users. Results Here, we present BAlaS, an interactive web application for performing CASM via BudeAlaScan and visualizing its results. BAlaS is interactive and intuitive to use. Results are displayed directly in the browser for the structure being interrogated enabling their rapid inspection. BAlaS has broad applications in areas, such as drug discovery and protein-interface design. Availability and implementation BAlaS works on all modern browsers and is available through the following website: https://balas.app. The project is open source, distributed using an MIT license and is available on GitHub (https://github.com/wells-wood-research/balas).

PPaxe: easy extraction of protein occurrence and interactions from the scientific literature

2018 ◽  
Vol 35 (14) ◽  
pp. 2523-2524 ◽  
Author(s):  
S Castillo-Lara ◽  
J F Abril
Keyword(s):  
Protein Interactions ◽  
Web Application ◽  
Scientific Literature ◽  
Supplementary Information ◽  
Command Line ◽  
Biological Processes ◽  
Supplementary Data ◽  
Protein Protein Interactions ◽  
Command Line Version

Abstract Motivation Protein–protein interactions (PPIs) are very important to build models for understanding many biological processes. Although several databases hold many of these interactions, exploring them, selecting those relevant for a given subject and contextualizing them can be a difficult task for researchers. Extracting PPIs directly from the scientific literature can be very helpful for providing such context, as the sentences describing these interactions may give insights to researchers in helpful ways. Results We have developed PPaxe, a python module and a web application that allows users to extract PPIs and protein occurrence from a given set of PubMed and PubMedCentral articles. It presents the results of the analysis in different ways to help researchers export, filter and analyze the results easily. Availability and implementation PPaxe web demo is freely available at https://compgen.bio.ub.edu/PPaxe. All the software can be downloaded from https://compgen.bio.ub.edu/PPaxe/download, including a command-line version and docker containers for an easy installation. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals PROTEINATOR: Web-UI exploring repurposing hypotheses of PROTEIN InhibiTORs based on protein interactions

2019 ◽  
Author(s):  
Santhosh Tangadu ◽  
Susmitha Shankara ◽  
Bhaskaram V. Varanasi ◽  
Prashanth Athri
Keyword(s):  
Drug Development ◽  
Search Engine ◽  
Protein Interactions ◽  
Web Application ◽  
Direct Interaction ◽  
Drug Repurposing ◽  
Protein S ◽  
Protein Protein Interactions ◽  
Integration Strategy ◽  
Data Analytic

AbstractPROTEINATOR is the first version of a staggered, multi-paradigm and extensible drug repurposing platform, focusing on a novel data analytic and integration strategy to find repurposing candidates that have potential to modulate targets through protein-protein interactions. The UI was created as an explorer to find ‘indirect’ drugs for a protein of interest. PROTEINATOR is developed as a web application that lets researchers search for alternate drugs for a protein of interest, based on the protein’s direct interaction with a another druggable protein. This unique tool provides researchers exploring specific implicated protein(s) (in the context of drug development), alternate, plausible routes to modulation by listing proteins that interact with the protein of interest that have reported inhibitors. It is a search engine to identify indirect drugs through connecting various databases, thus avoiding multiple steps and avoiding any manual errors. Using a representative set of databases, 112083 number of ‘indirect’ drug interactions are discovered that are potential modulators of proteins, detailed annotations of which are provided in the UI. PROTEINATOR is freely available at http://www.proteinator.in.

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