Epidemiological modeling in StochSS Live!

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.

Download Full-text

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

Bioinformatics ◽

10.1093/bioinformatics/btaa559 ◽

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.

Download Full-text

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

Bioinformatics ◽

10.1093/bioinformatics/bty967 ◽

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.

Download Full-text

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

Bioinformatics ◽

10.1093/bioinformatics/btz289 ◽

2019 ◽

Vol 35 (21) ◽

pp. 4501-4503 ◽

Cited By ~ 9

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.

Download Full-text

DrawGlycan-SNFG and gpAnnotate: rendering glycans and annotating glycopeptide mass spectra

Bioinformatics ◽

10.1093/bioinformatics/btz819 ◽

2019 ◽

Cited By ~ 4

Author(s):

Kai Cheng ◽

Gabrielle Pawlowski ◽

Xinheng Yu ◽

Yusen Zhou ◽

Sriram Neelamegham

Keyword(s):

Mass Spectrometry ◽

Open Source ◽

Mass Spectra ◽

Supplementary Information ◽

Supplementary Data ◽

International Union ◽

Open Source Program ◽

Source Program ◽

Wide Range ◽

Peptide Modifications

Abstract Summary This manuscript describes an open-source program, DrawGlycan-SNFG (version 2), that accepts IUPAC (International Union of Pure and Applied Chemist)-condensed inputs to render Symbol Nomenclature For Glycans (SNFG) drawings. A wide range of local and global options enable display of various glycan/peptide modifications including bond breakages, adducts, repeat structures, ambiguous identifications etc. These facilities make DrawGlycan-SNFG ideal for integration into various glycoinformatics software, including glycomics and glycoproteomics mass spectrometry (MS) applications. As a demonstration of such usage, we incorporated DrawGlycan-SNFG into gpAnnotate, a standalone application to score and annotate individual MS/MS glycopeptide spectrum in different fragmentation modes. Availability and implementation DrawGlycan-SNFG and gpAnnotate are platform independent. While originally coded using MATLAB, compiled packages are also provided to enable DrawGlycan-SNFG implementation in Python and Java. All programs are available from https://virtualglycome.org/drawglycan; https://virtualglycome.org/gpAnnotate. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

Download Full-text

LRez: C ++ API and toolkit for analyzing and managing Linked-Reads data

Bioinformatics Advances ◽

10.1093/bioadv/vbab022 ◽

2021 ◽

Author(s):

Pierre Morisse ◽

Claire Lemaitre ◽

Fabrice Legeai

Keyword(s):

Genome Assembly ◽

Low Cost ◽

Variant Calling ◽

Supplementary Information ◽

Supplementary Data ◽

High Quality ◽

Dna Molecule ◽

Sequencing Technologies ◽

Wide Range ◽

Genomic Regions

Abstract Motivation Linked-Reads technologies combine both the high-quality and low cost of short-reads sequencing and long-range information, through the use of barcodes tagging reads which originate from a common long DNA molecule. This technology has been employed in a broad range of applications including genome assembly, phasing and scaffolding, as well as structural variant calling. However, to date, no tool or API dedicated to the manipulation of Linked-Reads data exist. Results We introduce LRez, a C ++ API and toolkit which allows easy management of Linked-Reads data. LRez includes various functionalities, for computing numbers of common barcodes between genomic regions, extracting barcodes from BAM files, as well as indexing and querying BAM, FASTQ and gzipped FASTQ files to quickly fetch all reads or alignments containing a given barcode. LRez is compatible with a wide range of Linked-Reads sequencing technologies, and can thus be used in any tool or pipeline requiring barcode processing or indexing, in order to improve their performances. Availability and implementation LRez is implemented in C ++, supported on Unix-based platforms, and available under AGPL-3.0 License at https://github.com/morispi/LRez, and as a bioconda module. Supplementary information Supplementary data are available at Bioinformatics Advances

Download Full-text

SolupHred: a server to predict the pH-dependent aggregation of intrinsically disordered proteins

Bioinformatics ◽

10.1093/bioinformatics/btaa909 ◽

2020 ◽

Author(s):

Carlos Pintado ◽

Jaime Santos ◽

Valentín Iglesias ◽

Salvador Ventura

Keyword(s):

Intrinsically Disordered Proteins ◽

Disordered Proteins ◽

Supplementary Information ◽

Supplementary Data ◽

Solution Ph ◽

Predictive Tool ◽

Web Based ◽

Intrinsically Disordered ◽

Dependent Protein ◽

Ph Dependent

Abstract Summary Polypeptides are exposed to changing environmental conditions that modulate their intrinsic aggregation propensities. Intrinsically disordered proteins (IDPs) constitutively expose their aggregation determinants to the solvent, thus being especially sensitive to its fluctuations. However, solvent conditions are often disregarded in computational aggregation predictors. We recently developed a phenomenological model to predict IDPs' solubility as a function of the solution pH, which is based on the assumption that both protein lipophilicity and charge depend on this parameter. The model anticipated solubility changes in different IDPs accurately. In this application note, we present SolupHred, a web-based interface that implements the aforementioned theoretical framework into a predictive tool able to compute IDPs aggregation propensities as a function of pH. SolupHred is the first dedicated software for the prediction of pH-dependent protein aggregation. Availability and implementation The SolupHred web server is freely available for academic users at: https://ppmclab.pythonanywhere.com/SolupHred. It is platform-independent and does not require previous registration. Supplementary information Supplementary data are available at Bioinformatics online.

Download Full-text

PyRanges: efficient comparison of genomic intervals in Python

10.1101/609396 ◽

2019 ◽

Cited By ~ 1

Author(s):

Endre Bakken Stovner ◽

Pål Sætrom

Keyword(s):

Supplementary Information ◽

Supplementary Data ◽

Genomic Libraries ◽

Link Type ◽

Simple Set ◽

Set Operations ◽

Wide Range ◽

Genomic Analyses ◽

Associated Data ◽

Memory Efficient

AbstractSummaryComplex genomic analyses often use sequences of simple set operations like intersection, overlap, and nearest on genomic intervals. These operations, coupled with some custom programming, allow a wide range of analyses to be performed. To this end, we have written PyRanges, a data structure for representing and manipulating genomic intervals and their associated data in Python. Run single-threaded on binary set operations, PyRanges is in median 2.3-9.6 times faster than the popular R GenomicRanges library and is equally memory efficient; run multi-threaded on 8 cores, our library is up to 123 times faster. PyRanges is therefore ideally suited both for individual analyses and as a foundation for future genomic libraries in Python.AvailabilityPyRanges is available open-source under the MIT license at https://github.com/biocore-NTNU/pyranges and documentation exists at https://biocore-NTNU.github.io/pyranges/[email protected] informationSupplementary data are available.

Download Full-text

Triplet-based similarity score for fully multilabeled trees with poly-occurring labels

Bioinformatics ◽

10.1093/bioinformatics/btaa676 ◽

2020 ◽

Author(s):

Simone Ciccolella ◽

Giulia Bernardini ◽

Luca Denti ◽

Paola Bonizzoni ◽

Marco Previtali ◽

...

Keyword(s):

Open Source ◽

Evolutionary History ◽

Similarity Measures ◽

Real Data ◽

Similarity Score ◽

Supplementary Information ◽

Supplementary Data ◽

Wide Range ◽

Golden Standard ◽

History Of

Abstract Motivation The latest advances in cancer sequencing, and the availability of a wide range of methods to infer the evolutionary history of tumors, have made it important to evaluate, reconcile and cluster different tumor phylogenies. Recently, several notions of distance or similarities have been proposed in the literature, but none of them has emerged as the golden standard. Moreover, none of the known similarity measures is able to manage mutations occurring multiple times in the tree, a circumstance often occurring in real cases. Results To overcome these limitations, in this article, we propose MP3, the first similarity measure for tumor phylogenies able to effectively manage cases where multiple mutations can occur at the same time and mutations can occur multiple times. Moreover, a comparison of MP3 with other measures shows that it is able to classify correctly similar and dissimilar trees, both on simulated and on real data. Availability and implementation An open source implementation of MP3 is publicly available at https://github.com/AlgoLab/mp3treesim. Supplementary information Supplementary data are available at Bioinformatics online.

Download Full-text

PyRice: a Python package for querying Oryza sativa databases

Bioinformatics ◽

10.1093/bioinformatics/btaa694 ◽

2020 ◽

Author(s):

Quan Do ◽

Ho Bich Hai ◽

Pierre Larmande

Keyword(s):

Oryza Sativa ◽

Heterogeneous Data ◽

Supplementary Information ◽

Supplementary Data ◽

Web Based ◽

Domain Experts ◽

Heterogeneous Data Sources ◽

Query System ◽

Gene Information ◽

Python Package

Abstract Summary Currently, gene information available for Oryza sativa species is located in various online heterogeneous data sources. Moreover, methods of access are also diverse, mostly web-based and sometimes query APIs, which might not always be straightforward for domain experts. The challenge is to collect information quickly from these applications and combine it logically, to facilitate scientific research. We developed a Python package named PyRice, a unified programing API to access all supported databases at the same time with consistent output. PyRice design is modular and implements a smart query system, which fits the computing resources to optimize the query speed. As a result, PyRice is easy to use and produces intuitive results. Availability and implementation https://github.com/SouthGreenPlatform/PyRice. Supplementary information Supplementary data are available at Bioinformatics online.

Download Full-text

GAPIN: Grouped and Aligned Protein Interface Networks

10.1101/520833 ◽

2019 ◽

Author(s):

Biharck M. Araújo ◽

Aline L. Coelho ◽

Sabrina A. Silveira ◽

João P. R. Romanelli ◽

Raquel C. de Melo-Minardi ◽

...

Keyword(s):

Interaction Network ◽

Supplementary Information ◽

Protein Interface ◽

Supplementary Data ◽

Web Interface ◽

Web Based ◽

Structural Interaction ◽

Peptidase Inhibitor ◽

Supplementary Material ◽

Hydrophobic Patterns

AbstractSummaryGAPIN is a web-based application for structural interaction network analysis among any type of PDB molecules, regardless of whether their interfaces are between chain-chain or chain-ligand. A special emphasis is given to graph clustering, allowing users to scrutinize target contexts for ligand candidates. We show how GAPIN can be used to unveil underlying hydrophobic patterns on a set of peptidase-inhibitor complexes. In another experiment, we show there is a positive correlation between cluster sizes and the presence of druggable spots, indicating that the clustering may discriminate the higher complexity of these hot subnetworks.Availability and implementationGAPIN is freely available as an easy-to-use web interface at https://[email protected], [email protected] informationSupplementary data are available online.

Download Full-text