scholarly journals From command-line bioinformatics to bioGUI

2018 ◽  
Author(s):  
Markus Joppich ◽  
Ralf Zimmer
Keyword(s):  
Command Line ◽  
Interdisciplinary Work ◽  
Bioinformatic Tools ◽  
Interdisciplinary Field ◽  
Bioinformatics Tools ◽  
One Step ◽  
Microsoft Windows

Bioinformatics is a highly interdisciplinary field providing applications for scientists from many disciplines. Installing and starting applications on the command-line (CL) is a problem for many scientists, nonetheless, most methods are implemented with a CL interface only. Providing a GUI for bioinformatics applications is one step towards routinely making CL-only applications available to more scientists, and, thus towards a more effective interdisciplinary work. We identified two main problems for conveniently using CL bioinformatic tools: First, many tools work on UNIX-systems only, while many scientists use Microsoft Windows. Second, scientists refrain from using command-line tools which, however, could well support them in their research. Both issues are addressed by bioGUI. The bioGUI framework provides easy means to make CL tools available for most scientists, especially making use of Windows Subsystem for Linux, which provides a native Ubuntu bash on Windows. In addition, bioGUI templates are easily created (automatically), making this framework highly rewarding for developers. The bioGUI repository allows to install and use bioinformatics tools with just a few clicks.

scholarly journals From command-line bioinformatics to bioGUI

2018 ◽  
Author(s):  
Markus Joppich ◽  
Ralf Zimmer
Keyword(s):  
Command Line ◽  
Interdisciplinary Work ◽  
Bioinformatic Tools ◽  
Interdisciplinary Field ◽  
Bioinformatics Tools ◽  
One Step ◽  
Microsoft Windows

Bioinformatics is a highly interdisciplinary field providing applications for scientists from many disciplines. Installing and starting applications on the command-line (CL) is a problem for many scientists, nonetheless, most methods are implemented with a CL interface only. Providing a GUI for bioinformatics applications is one step towards routinely making CL-only applications available to more scientists, and, thus towards a more effective interdisciplinary work. We identified two main problems for conveniently using CL bioinformatic tools: First, many tools work on UNIX-systems only, while many scientists use Microsoft Windows. Second, scientists refrain from using command-line tools which, however, could well support them in their research. Both issues are addressed by bioGUI. The bioGUI framework provides easy means to make CL tools available for most scientists, especially making use of Windows Subsystem for Linux, which provides a native Ubuntu bash on Windows. In addition, bioGUI templates are easily created (automatically), making this framework highly rewarding for developers. The bioGUI repository allows to install and use bioinformatics tools with just a few clicks.

scholarly journals From command-line bioinformatics to bioGUI

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8111 ◽  
Author(s):  
Markus Joppich ◽  
Ralf Zimmer
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Command Line ◽  
Command Line Interface ◽  
Interdisciplinary Work ◽  
Interdisciplinary Field ◽  
Bioinformatics Tools ◽  
One Step ◽  
Microsoft Windows

Bioinformatics is a highly interdisciplinary field providing (bioinformatics) applications for scientists from many disciplines. Installing and starting applications on the command-line (CL) is inconvenient and/or inefficient for many scientists. Nonetheless, most methods are implemented with a command-line interface only. Providing a graphical user interface (GUI) for bioinformatics applications is one step toward routinely making CL-only applications available to more scientists and, thus, toward a more effective interdisciplinary work. With our bioGUI framework we address two main problems of using CL bioinformatics applications: First, many tools work on UNIX-systems only, while many scientists use Microsoft Windows. Second, scientists refrain from using CL tools which, however, could well support them in their research. With bioGUI install modules and templates, installing and using CL tools is made possible for most scientists—even on Windows, due to bioGUI’s support for Windows Subsystem for Linux. In addition, bioGUI templates can easily be created, making the bioGUI framework highly rewarding for developers. From the bioGUI repository it is possible to download, install and use bioinformatics tools with just a few clicks.

scholarly journals Alview: Portable Software for Viewing Sequence Reads in BAM Formatted Files

2015 ◽  
Vol 14 ◽  
pp. CIN.S26470 ◽  
Author(s):  
Richard P. Finney ◽  
Qing-Rong Chen ◽  
Cu V. Nguyen ◽  
Chih Hao Hsu ◽  
Chunhua Yan ◽  
...  
Keyword(s):  
Graphical User Interface ◽  
Reference Genome ◽  
Source Code ◽  
Software Tool ◽  
Command Line ◽  
Sequencing Data ◽  
Genome Data ◽  
Command Line Tool ◽  
Portable Software ◽  
Microsoft Windows

The name Alview is a contraction of the term Alignment Viewer. Alview is a compiled to native architecture software tool for visualizing the alignment of sequencing data. Inputs are files of short-read sequences aligned to a reference genome in the SAM/BAM format and files containing reference genome data. Outputs are visualizations of these aligned short reads. Alview is written in portable C with optional graphical user interface (GUI) code written in C, C++, and Objective-C. The application can run in three different ways: as a web server, as a command line tool, or as a native, GUI program. Alview is compatible with Microsoft Windows, Linux, and Apple OS X. It is available as a web demo at https://cgwb.nci.nih.gov/cgi-bin/alview . The source code and Windows/Mac/Linux executables are available via https://github.com/NCIP/alview .

scholarly journals An Overview of Bioinformatics Tools for DNA Meta-Barcoding Analysis of Microbial Communities of Bioaerosols: Digest for Microbiologists

Life ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 185
Author(s):  
Hamza Mbareche ◽  
Nathan Dumont-Leblond ◽  
Guillaume J. Bilodeau ◽  
Caroline Duchaine
Keyword(s):  
Microbial Communities ◽  
Microbial Ecology ◽  
Statistical Tests ◽  
Repeated Measurements ◽  
Microbial Composition ◽  
Alpha And Beta Diversity ◽  
Bioinformatic Tools ◽  
Bioinformatics Tools ◽  
Wide Range ◽  
Guided Tour

High-throughput DNA sequencing (HTS) has changed our understanding of the microbial composition present in a wide range of environments. Applying HTS methods to air samples from different environments allows the identification and quantification (relative abundance) of the microorganisms present and gives a better understanding of human exposure to indoor and outdoor bioaerosols. To make full use of the avalanche of information made available by these sequences, repeated measurements must be taken, community composition described, error estimates made, correlations of microbiota with covariates (variables) must be examined, and increasingly sophisticated statistical tests must be conducted, all by using bioinformatics tools. Knowing which analysis to conduct and which tools to apply remains confusing for bioaerosol scientists, as a litany of tools and data resources are now available for characterizing microbial communities. The goal of this review paper is to offer a guided tour through the bioinformatics tools that are useful in studying the microbial ecology of bioaerosols. This work explains microbial ecology features like alpha and beta diversity, multivariate analyses, differential abundances, taxonomic analyses, visualization tools and statistical tests using bioinformatics tools for bioaerosol scientists new to the field. It illustrates and promotes the use of selected bioinformatic tools in the study of bioaerosols and serves as a good source for learning the “dos and don’ts” involved in conducting a precise microbial ecology study.

scholarly journals ASaiM: a Galaxy-based framework to analyze raw shotgun data from microbiota

2017 ◽  
Author(s):  
Bérénice Batut ◽  
Kévin Gravouil ◽  
Clémence Defois ◽  
Saskia Hiltemann ◽  
Jean-François Brugère ◽  
...  
Keyword(s):  
Technological Progress ◽  
Source Code ◽  
Command Line ◽  
Bioinformatic Tools ◽  
Link Type ◽  
Data Analyses ◽  
The Galaxy ◽  
Sequencing Platforms ◽  
User Friendly ◽  
New Generation

AbstractBackgroundNew generation of sequencing platforms coupled to numerous bioinformatics tools has led to rapid technological progress in metagenomics and metatranscriptomics to investigate complex microorganism communities. Nevertheless, a combination of different bioinformatic tools remains necessary to draw conclusions out of microbiota studies. Modular and user-friendly tools would greatly improve such studies.FindingsWe therefore developed ASaiM, an Open-Source Galaxy-based framework dedicated to microbiota data analyses. ASaiM provides a curated collection of tools to explore and visualize taxonomic and functional information from raw amplicon, metagenomic or metatranscriptomic sequences. To guide different analyses, several customizable workflows are included. All workflows are supported by tutorials and Galaxy interactive tours to guide the users through the analyses step by step. ASaiM is implemented as Galaxy Docker flavour. It is scalable to many thousand datasets, but also can be used a normal PC. The associated source code is available under Apache 2 license at https://github.com/ASaiM/framework and documentation can be found online (http://asaim.readthedocs.io/)ConclusionsBased on the Galaxy framework, ASaiM offers sophisticated analyses to scientists without command-line knowledge. ASaiM provides a powerful framework to easily and quickly explore microbiota data in a reproducible and transparent environment.

scholarly journals Bioinformatic tools for cancer geneticists

2005 ◽  
Vol 13 (2) ◽  
pp. 69-75 ◽  
Author(s):  
Karmen Stankov
Keyword(s):  
Predictive Power ◽  
Expression Patterns ◽  
Medical Science ◽  
Patient Treatment ◽  
Molecular Characteristics ◽  
Specific Patient ◽  
Bioinformatic Tools ◽  
Control And Prevention ◽  
One Step ◽  
Detection Of Mutations

Early detection is essential for the control and prevention of many diseases, particularly cancer, which is the reason why the need for new disease markers with improved sensitivity and specificity continues to grow. Utilization of sophisticated bioinformatic tools enables the increased specificity and a relatively large quantity of high quality assays for any gene of interest. Understanding the molecular characteristics of diseases, such as cancer and the detection of mutations or changes in gene expression patterns that occur as a result of the disease, will bring researchers one step closer to achieving the predictive power needed for the development of new therapies, the design of clinical trials, and specific patient treatment planning. Genetic screening is one of the fastest moving areas of medical science, particularly in oncology, and as more genes are cloned, and more disease-associated mutations discovered, the workload is set to increase considerably with the utilization of bioinformatics tools used in integration and analysis of genomic, proteomic and metabolomic profiles of cancer. .

scholarly journals Effectiveness and Usability of Bioinformatics Tools to Analyze Pathways Associated with miRNA Expression

2015 ◽  
Vol 14 ◽  
pp. CIN.S32716 ◽  
Author(s):  
Lila E. Mullany ◽  
Roger K. Wolff ◽  
Martha L. Slattery
Keyword(s):  
Gene Ontology ◽  
Gene Regulation ◽  
Mirna Expression ◽  
Biological Pathways ◽  
Colorectal Tumors ◽  
Rna Molecules ◽  
General Lack ◽  
Bioinformatic Tools ◽  
Bioinformatics Tools ◽  
Differentially Expressed Mirnas

MiRNAs are small, nonprotein-coding RNA molecules involved in gene regulation. While bioinformatics help guide miRNA research, it is less clear how they perform when studying biological pathways. We used 13 criteria to evaluate effectiveness and usability of existing bioinformatics tools. We evaluated the performance of six bioinformatics tools with a cluster of 12 differentially expressed miRNAs in colorectal tumors and three additional sets of 12 miRNAs that are not part of a known cluster. MiRPath performed the best of all the tools in linking miRNAs, with 92% of all miRNAs linked as well as the highest based on our established criteria followed by Ingenuity (58% linked). Other tools, including Empirical Gene Ontology, miRó, miRMaid, and PhenomiR, were limited by their lack of available tutorials, lack of flexibility and interpretability, and/or difficulty using the tool. In summary, we observed a lack of standardization across bioinformatic tools and a general lack of specificity in terms of pathways identified between groups of miRNAs. Hopefully, this evaluation will help guide the development of new tools.

scholarly journals Validation of new bioinformatic tools to identify expanded repeats: a non-reference intronic pentamer expansion inRFC1causes CANVAS

2019 ◽  
Author(s):  
Haloom Rafehi ◽  
David J Szmulewicz ◽  
Mark F Bennett ◽  
Nara LM Sobreira ◽  
Kate Pope ◽  
...  
Keyword(s):  
Genetic Basis ◽  
Clinical Medicine ◽  
Whole Genome Sequence ◽  
Reference Sequence ◽  
Gene Encoding ◽  
Bioinformatic Tools ◽  
Genomic Technologies ◽  
Bioinformatics Tools ◽  
Alu Element ◽  
Repeat Expansions

ABSTRACTGenomic technologies such as Next Generation Sequencing (NGS) are revolutionizing molecular diagnostics and clinical medicine. However, these approaches have proven inefficient at identifying pathogenic repeat expansions. Here, we apply a collection of bioinformatics tools that can be utilized to identify either known or novel expanded repeat sequences in NGS data. We performed genetic studies of a cohort of 35 individuals from 22 families with a clinical diagnosis of cerebellar ataxia with neuropathy and bilateral vestibular areflexia syndrome (CANVAS). Analysis of whole genome sequence (WGS) data with five independent algorithms identified a recessively inherited intronic repeat expansion [(AAGGG)exp] in the gene encoding Replication Factor C1 (RFC1). This motif, not reported in the reference sequence, localized to an Alu element and replaced the reference (AAAAG)11short tandem repeat. Genetic analyses confirmed the pathogenic expansion in 18 of 22 CANVAS families and identified a core ancestral haplotype, estimated to have arisen in Europe over twenty-five thousand years ago. WGS of the fourRFC1negative CANVAS families identified plausible variants in three, with genomic re-diagnosis of SCA3, spastic ataxia of the Charlevoix-Saguenay type and SCA45. This study identified the genetic basis of CANVAS and demonstrated that these improved bioinformatics tools increase the diagnostic utility of WGS to determine the genetic basis of a heterogeneous group of clinically overlapping neurogenetic disorders.

scholarly journals Tailoring Educational Elements for Academic Teaching - The JurMOO

10.28945/2546 ◽  
2002 ◽  
Author(s):  
Bernhard Nett ◽  
Birgit Huber ◽  
Susanne Knirsch ◽  
Léa Meyer ◽  
Bernd Remmele ◽  
...  
Keyword(s):  
Online Learning ◽  
Educational Material ◽  
Gender Mainstreaming ◽  
Web Based ◽  
Academic Teaching ◽  
Interdisciplinary Field ◽  
One Step ◽  
And Gender ◽  
The Web ◽  
The Ideal

The RION project (financed by BMBF) aims at improving Computer & Law (C&L) teaching in Germany while implementing Web-based media. For the fluid and interdisciplinary field of C&L, educational material is very scarce. Furthermore, educational cultures differ according to the divers affiliations of C&L. Therefore, the RION platform will present a variety of documents online, which have not been accessible on the Web before. However, publishing law collections online can only be one step to improve C&L teaching. Therefore, RION is trying to develop a didactical conception for the new platform, the main focus being on cooperative, practice-oriented learning and gender mainstreaming. Due to the diversity and the constraints given in the project, the RION team does not look for the "ideal platform", but instead tries to tailor promising elements of possible C&L online learning. In this text, the example of JurMOO, which we tested in C&L teaching, is used to demonstrate this.

scholarly journals The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities

2019 ◽  
Author(s):  
James J Davis ◽  
Alice R Wattam ◽  
Ramy K Aziz ◽  
Thomas Brettin ◽  
Ralph Butler ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Cost Effective ◽  
Command Line ◽  
Web Based ◽  
The Public ◽  
Bioinformatic Tools ◽  
Resource Center ◽  
Bioinformatics Resource ◽  
Analysis Tools ◽  
Analysis Environment

Abstract The PathoSystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center funded by the National Institute of Allergy and Infectious Diseases (https://www.patricbrc.org). PATRIC supports bioinformatic analyses of all bacteria with a special emphasis on pathogens, offering a rich comparative analysis environment that provides users with access to over 250 000 uniformly annotated and publicly available genomes with curated metadata. PATRIC offers web-based visualization and comparative analysis tools, a private workspace in which users can analyze their own data in the context of the public collections, services that streamline complex bioinformatic workflows and command-line tools for bulk data analysis. Over the past several years, as genomic and other omics-related experiments have become more cost-effective and widespread, we have observed considerable growth in the usage of and demand for easy-to-use, publicly available bioinformatic tools and services. Here we report the recent updates to the PATRIC resource, including new web-based comparative analysis tools, eight new services and the release of a command-line interface to access, query and analyze data.

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