scholarly journals geneCo: a visualized comparative genomic method to analyze multiple genome structures

2019 ◽  
Vol 35 (24) ◽  
pp. 5303-5305 ◽  
Author(s):  
Jaehee Jung ◽  
Jong Im Kim ◽  
Gangman Yi
Keyword(s):  
Genome Structure ◽  
Software Tool ◽  
Detailed Comparison ◽  
Supplementary Information ◽  
Comparative Genomic ◽  
Web Based ◽  
Computational Environment ◽  
Gene Comparison ◽  
User Data ◽  
Gain Loss

Abstract Summary In comparative and evolutionary genomics, a detailed comparison of common features between organisms is essential to evaluate genetic distance. However, identifying differences in matched and mismatched genes among multiple genomes is difficult using current comparative genomic approaches due to complicated methodologies or the generation of meager information from obtained results. This study describes a visualized software tool, geneCo (gene Comparison), for comparing genome structure and gene arrangements between various organisms. User data are aligned, gene information is recognized, and genome structures are compared based on user-defined GenBank files. Information regarding inversion, gain, loss, duplication and gene rearrangement among multiple organisms being compared is provided by geneCo, which uses a web-based interface that users can easily access without any need to consider the computational environment. Availability and implementation Users can freely use the software, and the accessible URL is https://bigdata.dongguk.edu/geneCo. The main module of geneCo is implemented by Python and the web-based user interface is built by PHP, HTML and CSS to support all browsers. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals ccNetViz: a WebGL-based JavaScript library for visualization of large networks

2020 ◽  
Vol 36 (16) ◽  
pp. 4527-4529
Author(s):  
Ales Saska ◽  
David Tichy ◽  
Robert Moore ◽  
Achilles Rasquinha ◽  
Caner Akdas ◽  
...  
Keyword(s):  
Systems Biology ◽  
Complex Networks ◽  
Open Source ◽  
High Speed ◽  
A Priori ◽  
Supplementary Information ◽  
Network Visualization ◽  
Supplementary Data ◽  
Web Based ◽  
Flow Of Information

Abstract Summary Visualizing a network provides a concise and practical understanding of the information it represents. Open-source web-based libraries help accelerate the creation of biologically based networks and their use. ccNetViz is an open-source, high speed and lightweight JavaScript library for visualization of large and complex networks. It implements customization and analytical features for easy network interpretation. These features include edge and node animations, which illustrate the flow of information through a network as well as node statistics. Properties can be defined a priori or dynamically imported from models and simulations. ccNetViz is thus a network visualization library particularly suited for systems biology. Availability and implementation The ccNetViz library, demos and documentation are freely available at http://helikarlab.github.io/ccNetViz/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals MODER2: first-order Markov modeling and discovery of monomeric and dimeric binding motifs

2020 ◽  
Vol 36 (9) ◽  
pp. 2690-2696
Author(s):  
Jarkko Toivonen ◽  
Pratyush K Das ◽  
Jussi Taipale ◽  
Esko Ukkonen
Keyword(s):  
Markov Models ◽  
Expectation Maximization Algorithm ◽  
Software Tool ◽  
Specific Weight ◽  
Training Data ◽  
Supplementary Information ◽  
Markov Modeling ◽  
Binding Motifs ◽  
The Difference ◽  
Probability Matrices

Abstract Motivation Position-specific probability matrices (PPMs, also called position-specific weight matrices) have been the dominating model for transcription factor (TF)-binding motifs in DNA. There is, however, increasing recent evidence of better performance of higher order models such as Markov models of order one, also called adjacent dinucleotide matrices (ADMs). ADMs can model dependencies between adjacent nucleotides, unlike PPMs. A modeling technique and software tool that would estimate such models simultaneously both for monomers and their dimers have been missing. Results We present an ADM-based mixture model for monomeric and dimeric TF-binding motifs and an expectation maximization algorithm MODER2 for learning such models from training data and seeds. The model is a mixture that includes monomers and dimers, built from the monomers, with a description of the dimeric structure (spacing, orientation). The technique is modular, meaning that the co-operative effect of dimerization is made explicit by evaluating the difference between expected and observed models. The model is validated using HT-SELEX and generated datasets, and by comparing to some earlier PPM and ADM techniques. The ADM models explain data slightly better than PPM models for 314 tested TFs (or their DNA-binding domains) from four families (bHLH, bZIP, ETS and Homeodomain), the ADM mixture models by MODER2 being the best on average. Availability and implementation Software implementation is available from https://github.com/jttoivon/moder2. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Epidemiological modeling in StochSS Live!

2021 ◽  
Author(s):  
Richard Jiang ◽  
Bruno Jacob ◽  
Matthew Geiger ◽  
Sean Matthew ◽  
Bryan Rumsey ◽  
...  
Keyword(s):  
Stochastic Model ◽  
Epidemiological Model ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Web Based ◽  
Epidemiological Modeling ◽  
Modeling Simulation ◽  
Wide Range ◽  
Biochemical Systems

Abstract Summary We present StochSS Live!, a web-based service for modeling, simulation and analysis of a wide range of mathematical, biological and biochemical systems. Using an epidemiological model of COVID-19, we demonstrate the power of StochSS Live! to enable researchers to quickly develop a deterministic or a discrete stochastic model, infer its parameters and analyze the results. Availability and implementation StochSS Live! is freely available at https://live.stochss.org/ Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals CNV-BAC: Copy number Variation Detection in Bacterial Circular Genome

2020 ◽  
Vol 36 (12) ◽  
pp. 3890-3891
Author(s):  
Linjie Wu ◽  
Han Wang ◽  
Yuchao Xia ◽  
Ruibin Xi
Keyword(s):  
Copy Number Variation ◽  
Copy Number ◽  
Genome Structure ◽  
Real Data ◽  
Read Depth ◽  
Supplementary Information ◽  
Circular Genome ◽  
Number Variation ◽  
Copy Number Variation Detection ◽  
Cnv Detection

Abstract Motivation Whole-genome sequencing (WGS) is widely used for copy number variation (CNV) detection. However, for most bacteria, their circular genome structure and high replication rate make reads more enriched near the replication origin. CNV detection based on read depth could be seriously influenced by such replication bias. Results We show that the replication bias is widespread using ∼200 bacterial WGS data. We develop CNV-BAC (CNV-Bacteria) that can properly normalize the replication bias and other known biases in bacterial WGS data and can accurately detect CNVs. Simulation and real data analysis show that CNV-BAC achieves the best performance in CNV detection compared with available algorithms. Availability and implementation CNV-BAC is available at https://github.com/XiDsLab/CNV-BAC. Supplementary information Supplementary data are available at Bioinformatics online.

CPVA: a web-based metabolomic tool for chromatographic peak visualization and annotation

2020 ◽  
Vol 36 (12) ◽  
pp. 3913-3915
Author(s):  
Hemi Luan ◽  
Xingen Jiang ◽  
Fenfen Ji ◽  
Zhangzhang Lan ◽  
Zongwei Cai ◽  
...  
Keyword(s):  
False Positive ◽  
Supplementary Information ◽  
Liquid Chromatography Mass Spectrometry ◽  
Targeted Metabolomics ◽  
Metabolomics Data ◽  
Web Based ◽  
Tremendous Amount ◽  
Chromatographic Peaks ◽  
User Friendly

Abstract Motivation Liquid chromatography–mass spectrometry-based non-targeted metabolomics is routinely performed to qualitatively and quantitatively analyze a tremendous amount of metabolite signals in complex biological samples. However, false-positive peaks in the datasets are commonly detected as metabolite signals by using many popular software, resulting in non-reliable measurement. Results To reduce false-positive calling, we developed an interactive web tool, termed CPVA, for visualization and accurate annotation of the detected peaks in non-targeted metabolomics data. We used a chromatogram-centric strategy to unfold the characteristics of chromatographic peaks through visualization of peak morphology metrics, with additional functions to annotate adducts, isotopes and contaminants. CPVA is a free, user-friendly tool to help users to identify peak background noises and contaminants, resulting in decrease of false-positive or redundant peak calling, thereby improving the data quality of non-targeted metabolomics studies. Availability and implementation The CPVA is freely available at http://cpva.eastus.cloudapp.azure.com. Source code and installation instructions are available on GitHub: https://github.com/13479776/cpva. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals TriPOINT: a software tool to prioritize important genes in pathways and their non-coding regulators

2018 ◽  
Vol 35 (15) ◽  
pp. 2686-2689
Author(s):  
Asa Thibodeau ◽  
Dong-Guk Shin
Keyword(s):  
Gene Expression ◽  
Software Tool ◽  
Supplementary Information ◽  
Analysis Tool ◽  
Graph Representations ◽  
Expression Levels ◽  
Conducting Pathway ◽  
Pathway Analysis Tool ◽  
Pathway Analyses ◽  
Gene Expression Levels

Abstract Summary Current approaches for pathway analyses focus on representing gene expression levels on graph representations of pathways and conducting pathway enrichment among differentially expressed genes. However, gene expression levels by themselves do not reflect the overall picture as non-coding factors play an important role to regulate gene expression. To incorporate these non-coding factors into pathway analyses and to systematically prioritize genes in a pathway we introduce a new software: Triangulation of Perturbation Origins and Identification of Non-Coding Targets. Triangulation of Perturbation Origins and Identification of Non-Coding Targets is a pathway analysis tool, implemented in Java that identifies the significance of a gene under a condition (e.g. a disease phenotype) by studying graph representations of pathways, analyzing upstream and downstream gene interactions and integrating non-coding regions that may be regulating gene expression levels. Availability and implementation The TriPOINT open source software is freely available at https://github.uconn.edu/ajt06004/TriPOINT under the GPL v3.0 license. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals TFEA.ChIP: a tool kit for transcription factor binding site enrichment analysis capitalizing on ChIP-seq datasets

2019 ◽  
Vol 35 (24) ◽  
pp. 5339-5340 ◽  
Author(s):  
Laura Puente-Santamaria ◽  
Wyeth W Wasserman ◽  
Luis del Peso
Keyword(s):  
Genomic Analysis ◽  
Enrichment Analysis ◽  
R Package ◽  
Supplementary Information ◽  
Web Based ◽  
Factor Binding Site ◽  
Gene Sets ◽  
Transcription Regulators ◽  
Computational Identification ◽  
On Chip

Abstract Summary The computational identification of the transcription factors (TFs) [more generally, transcription regulators, (TR)] responsible for the co-regulation of a specific set of genes is a common problem found in genomic analysis. Herein, we describe TFEA.ChIP, a tool that makes use of ChIP-seq datasets to estimate and visualize TR enrichment in gene lists representing transcriptional profiles. We validated TFEA.ChIP using a wide variety of gene sets representing signatures of genetic and chemical perturbations as input and found that the relevant TR was correctly identified in 126 of a total of 174 analyzed. Comparison with other TR enrichment tools demonstrates that TFEA.ChIP is an highly customizable package with an outstanding performance. Availability and implementation TFEA.ChIP is implemented as an R package available at Bioconductor https://www.bioconductor.org/packages/devel/bioc/html/TFEA.ChIP.html and github https://github.com/LauraPS1/TFEA.ChIP_downloads. A web-based GUI to the package is also available at https://www.iib.uam.es/TFEA.ChIP/ Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals BIOLITMAP: a web-based geolocated, temporal and thematic visualization of the evolution of bioinformatics publications

2018 ◽  
Vol 35 (14) ◽  
pp. 2518-2520
Author(s):  
Adrián Bazaga ◽  
Alfonso Valencia ◽  
María- JoséRementeria
Keyword(s):  
General Public ◽  
Fast Growth ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Web Based ◽  
Research Publications

Abstract Motivation The fast growth of bioinformatics adds a significant difficulty to assess the contribution, geographical and thematic distribution of the research publications. Results To help researchers, grant agencies and general public to assess the progress in bioinformatics, we have developed BIOLITMAP, a web-based geolocation system that allows an easy and sensible exploration of the publications by institution, year and topic. Availability and implementation BIOLITMAP is available at http://socialanalytics.bsc.es/biolitmap and the sources have been deposited at https://github.com/inab/BIOLITMAP. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Web-Based Simulation Environment for Vehicular Electrical Networks

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6087
Author(s):  
Xavier Dominguez ◽  
Paola Mantilla-Pérez ◽  
Nuria Gimenez ◽  
Islam El-Sayed ◽  
Manuel Alberto Díaz Díaz Millán ◽  
...  
Keyword(s):  
Visual Analytics ◽  
Distribution Systems ◽  
Software Tool ◽  
Automatic Generation ◽  
Electrical Networks ◽  
Web Based ◽  
Electrical Distribution Systems ◽  
Technical Requirements ◽  
Information Interaction

For the validation of vehicular Electrical Distribution Systems (EDS), engineers are currently required to analyze disperse information regarding technical requirements, standards and datasheets. Moreover, an enormous effort takes place to elaborate testing plans that are representative for most EDS possible configurations. These experiments are followed by laborious data analysis. To diminish this workload and the need for physical resources, this work reports a simulation platform that centralizes the tasks for testing different EDS configurations and assists the early detection of inadequacies in the design process. A specific procedure is provided to develop a software tool intended for this aim. Moreover, the described functionalities are exemplified considering as a case study the main wire harness from a commercial vehicle. A web-based architecture has been employed in alignment with the ongoing software development revolution and thus provides flexibility for both, developers and users. Due to its scalability, the proposed software scheme can be extended to other web-based simulation applications. Furthermore, the automatic generation of electrical layouts for EDS is addressed to favor an intuitive understanding of the network. To favor human–information interaction, utilized visual analytics strategies are also discussed. Finally, full simulation workflows are exposed to provide further insights on the deployment of this type of computer platforms.

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