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bioinformatics tools and Databases for Genomics-assisted Breeding and Population Genetics of Plants: A Review

CURRENT bioinformatics 2021年第6期16卷 766-773页

作者： Aglawe, Supriya Babasaheb Verma, Amit Kumar Upadhyay, Atul Kumar Indian Inst Sci Educ & Res Tirupati 517507 Andhra Pradesh India Indian Inst Sci Educ & Res Bhopal Madhya Pradesh India Thapar Inst Engn & Technol Dept Biotechnol Patiala Punjab India

Genomics is the study of the complete genetic material of an organism. It would not be an exaggeration to say that we are at the peak of the genomics era as with the advent of high-throughput sequencing technologies we have an enormous amount of genomic data coming every day. Genomics assisted breeding (GAB) is becoming increasingly popular in the field of crop improvement. GAB utilizes available genomics information of different crops and their relatives for the purpose of plant breeding to produce improved varieties of the crops. Proper knowledge of these tools and databases helps in speeding up the process of plant breeding. The available tools can be categorized into several groups such as genetic diversity, Quantitative Trait Locus (QTL)/gene mapping, Next-Generation Sequencing (NGS) based Single Nucleotide Polymorphism (SNP) genotyping, Molecular breeding, Genome-Wide Association Studies (GWAS), Genomic Selection (GS), Marker-Assisted Recurrent Selection (MARS), Multiparent Advanced Generation Inter-Cross (MAGIC), etc. Most of the available tools are user friendly and where it is not, needs to be updated soon. There is an urgent need to develop the scientific resources and technical expertise for the proper and effective use of these tools. In this review, we have extensively covered the available tools and databases for the genomic assisted breeding and population genetics study of the plants. The details of these tools and databases along with their web links are also provided. We believe this review will be handy and useful for the scientists and researches of plant breeding, population genetics, and genomics.

关键词： Genome Assisted Breeding (GAB) bioinformatics tools genomics plant breeding genetics molecular

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miRNA, siRNA, and lncRNA: Recent Development of bioinformatics tools and Databases in Support of Combating Different Diseases

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CURRENT bioinformatics 2024年第1期19卷 39-60页

作者： Chakraborty, Chiranjib Bhattacharya, Manojit Sharma, Ashish Ranjan Adamas Univ Sch Life Sci & Biotechnol Dept Biotechnol Kolkata 700126 W Bengal India Fakir Mohan Univ Dept Zool Balasore 756020 Orissa India Hallym Univ Chuncheon Sacred Heart Hosp Inst Skeletal Aging & Orthopaed Surg Chuncheon Si 24252 Gangwon Do South Korea

Today, the bioinformatics tool and database development are one of the most significant research areas in computational biology. Computational biologists are developing diverse bioinformatics tools and databases in the various fields of biological science. Nowadays, several non-coding RNAs (ncRNA) have been studied extensively, which act as a mediator of the regulation of gene expression. ncRNA is a functional RNA molecule that is transcribed from the mammalian genome. It also controls the disease regulation pathway. Based on the size, ncRNA can be classified into three categories such as small ncRNA (similar to 18-30 nt), medium ncRNA (similar to 30-200 nt), and long ncRNA (from 200 nt to several hundred kb). The miRNA and siRNAs are two types of ncRNA. Various bioinformatics tools and databases have recently been developed to understand the different ncRNAs (miRNAs, siRNAs, and lncRNAs) disease association. We have illustrated different bioinformatics resources, such as in silico tools and databases, currently available for researching miRNAs, siRNAs, and lncRNAs. Some bioinformatics-based miRNA tools are miRbase, miRecords, miRCancer, miRSystem, miRGator, miRNEST, mirtronPred and miRIAD, etc. bioinformatics-based siRNA tools are siPRED, siDRM, sIR, siDirect 2.0. bioinformatics-based lncRNAs tools are lncRNAdb v2, lncRNAtor, LncDisease, iLoc-lncRNA, etc. These tools and databases benefit molecular biologists, biomedical researchers, and computational biologists.

关键词： bioinformatics tools databases siRNA miRNAs lncRNA computational biology

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Comparative Modeling of Proteins: A Method for Engaging Students' Interest in bioinformatics tools

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BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION 2014年第1期42卷 68-78页

作者： Badotti, Fernanda Barbosa, Alan Sales Martins Reis, Andre Luiz do Valle, Italo Faria Ambrosio, Lara Bitar, Maina Fundacao Oswaldo Cruz FIOCRUZ MG Ctr Excelencia Bioinformat CEBio Belo Horizonte MG Brazil Univ Fed Minas Gerais Dept Fisiol & Biofis Belo Horizonte MG Brazil Univ Fed Minas Gerais Dept Bioquim & Imunol Belo Horizonte MG Brazil Univ Fed Minas Gerais Dept Microbiol Belo Horizonte MG Brazil

The huge increase in data being produced in the genomic era has produced a need to incorporate computers into the research process. Sequence generation, its subsequent storage, interpretation, and analysis are now entirely computer-dependent tasks. Universities from all over the world have been challenged to seek a way of encouraging students to incorporate computational and bioinformatics skills since undergraduation in order to understand biological processes. The aim of this article is to report the experience of awakening students' interest in bioinformatics tools during a course focused on comparative modeling of proteins. The authors start by giving a full description of the course environmental context and students' backgrounds. Then they detail each class and present a general overview of the protein modeling protocol. The positive and negative aspects of the course are also reported, and some of the results generated in class and in projects outside the classroom are discussed. In the last section of the article, general perspectives about the course from students' point of view are given. This work can serve as a guide for professors who teach subjects for which bioinformatics tools are useful and for universities that plan to incorporate bioinformatics into the curriculum. (c) 2013 by The International Union of Biochemistry and Molecular Biology, 42(1):68-78, 2014

关键词： protein modeling bioinformatics tools bioinformatics teaching

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How do I get the most out of my protein sequence using bioinformatics tools?

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ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY 2021年第9期77卷 1116-1126页

作者： Pereira, Joana Alva, Vikram Max Planck Inst Dev Biol Dept Prot Evolut Max Planck Ring 5 D-72076 Tubingen Germany Univ Basel Biozentrum CH-4056 Basel Switzerland

Biochemical and biophysical experiments are essential for uncovering the three-dimensional structure and biological role of a protein of interest. However, meaningful predictions can frequently also be made using bioinformatics resources that transfer knowledge from a well studied protein to an uncharacterized protein based on their evolutionary relatedness. These predictions are helpful in developing specific hypotheses to guide wet-laboratory experiments. Commonly used bioinformatics resources include methods to identify and predict conserved sequence motifs, protein domains, transmembrane segments, signal sequences, and secondary as well as tertiary structure. Here, several such methods available through the MPI bioinformatics Toolkit (https://*** ) are described and how their combined use can provide meaningful information on a protein of unknown function is demonstrated. In particular, the identification of homologs of known structure using HHpred, internal repeats using HHrepID, coiled coils using PCOILS and DeepCoil, and transmembrane segments using Quick2D are focused on.

关键词： deep homology searches protein sequence annotation homology modeling coiled coils sequence features bioinformatics tools

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Trends in the development of miRNA bioinformatics tools

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BRIEFINGS IN bioinformatics 2019年第5期20卷 1836-1852页

作者： Chen, Liang Heikkinen, Liisa Wang, Changliang Yang, Yang Sun, Huiyan Wong, Garry Univ Macau Fac Hlth Sci E12 Ave Univ Taipa Macau Peoples R China Jilin Univ Coll Comp Sci & Technol Changchun Peoples R China

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression via recognition of cognate sequences and interference of transcriptional, translational or epigenetic processes. bioinformatics tools developed for miRNA study include those for miRNA prediction and discovery, structure, analysis and target prediction. We manually curated 95 review papers and similar to 1000 miRNA bioinformatics tools published since 2003. We classified and ranked them based on citation number or Page Rank score, and then performed network analysis and text mining (TM) to study the miRNA tools development trends. Five key trends were observed: (1) miRNA identification and target prediction have been hot spots in the past decade;(2) manual curation and TM are the main methods for collecting miRNA knowledge from literature;(3) most early tools are well maintained and widely used;(4) classic machine learning methods retain their utility;however, novel ones have begun to emerge;(5) disease-associated miRNA tools are emerging. Our analysis yields significant insight into the past development and future directions of miRNA tools.

关键词： miRNA bioinformatics tools text mining bibliometric ranking

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Evaluation of somatic copy number variation detection by NGS technologies and bioinformatics tools on a hyper-diploid cancer genome

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GENOME BIOLOGY 2024年第1期25卷 1页

作者： Masood, Daniall Ren, Luyao Nguyen, Cu Brundu, Francesco G. Zheng, Lily Zhao, Yongmei Jaeger, Erich Li, Yong Cha, Seong Won Halpern, Aaron Truong, Sean Virata, Michael Yan, Chunhua Chen, Qingrong Pang, Andy Alberto, Reyes Xiao, Chunlin Yang, Zhaowei Chen, Wanqiu Wang, Charles Cross Jr, Frank Catreux, Severine Shi, Leming Beaver, Julia A. Xiao, Wenming Meerzaman, Daoud M. US FDA Off Oncol Dis Off New Drug Ctr Drug Evaluat & Res 10903 New Hampshire Ave Silver Spring MD 20993 USA Fudan Univ Human Phenome Inst Sch Life Sci State Key Lab Genet Engn Shanghai Peoples R China Fudan Univ Shanghai Canc Ctr Shanghai Peoples R China NCI Computat Genom & Bioinformat Branch Ctr Biomed Informat & Informat Technol CBIIT Rockville MD 20850 USA Illumina Inc San Diego CA USA Frederick Natl Lab Canc Res Sequencing Facil Bioinformat Grp Biomed Informat & Data Sci Directorate Frederick MD USA Bionano Genom San Diego CA 20892 USA NIH Natl Ctr Biotechnol Informat Natl Lib Med Bethesda MD 20892 USA Loma Linda Univ Sch Med Ctr Genom Loma Linda CA USA US FDA Oncol Ctr Excellence Silver Spring MD USA

Background Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data sets established in our previous study, we benchmark the performance of cancer CNV calling by six most recent and commonly used software tools on their detection accuracy, sensitivity, and reproducibility. In comparison to other orthogonal methods, such as microarray and Bionano, we also explore the consistency of CNV calling across different technologies on a challenging *** While consistent results are observed for copy gain, loss, and loss of heterozygosity (LOH) calls across sequencing centers, CNV callers, and different technologies, variation of CNV calls are mostly affected by the determination of genome ploidy. Using consensus results from six CNV callers and confirmation from three orthogonal methods, we establish a high confident CNV call set for the reference cancer cell line (HCC1395).Conclusions NGS technologies and current bioinformatics tools can offer reliable results for detection of copy gain, loss, and LOH. However, when working with a hyper-diploid genome, some software tools can call excessive copy gain or loss due to inaccurate assessment of genome ploidy. With performance matrices on various experimental conditions, this study raises awareness within the cancer research community for the selection of sequencing platforms, sample preparation, sequencing coverage, and the choice of CNV detection tools.

关键词： Copy number variation Cancer genome Next-generation sequencing bioinformatics tools Consistency Accuracy Reproducibility Detection sensitivity Genome ploidy

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CRISPR-Cas9 sgRNA design and outcome assessment: bioinformatics tools and aquaculture applications

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Aquaculture and Fisheries 2022年第2期7卷 121-130页

作者： Mingkun Luo Jun Wang Zaijie Dong Chenghui Wang Guoqing Lu Key Laboratory of Freshwater Fisheries and Germplasm Resources Utilization Freshwater Fisheries Research Centre of Chinese Academy of Fishery SciencesMinistry of Agriculture and Rural AffairsWuxi214081China Key Laboratory of Freshwater Aquatic Genetic Resources Ministry of Agriculture and Rural Affairs/National Demonstration Center for Experimental Fisheries Science Education/Shanghai Engineering Research Center of AquacultureShanghai Ocean UniversityShanghai201306China Department of Biology University of Nebraska at OmahaOmahaNE68182USA

The CRISPR-Cas9 genome editing has many advantages over its counterparts and could ultimately assist in disease control and molecular breeding in ***-guide RNA(sgRNA)design is presumably the most crucial task in a typical CRISPR-Cas9 experiment;an understanding of algorithms behind sgRNA design programs is thus essential for improved efficacy and *** focus this review on the bioinformatics aspects in genome editing experiments and describe commonly used computational approaches and tools of sgRNA design and outcome *** show an example of sgRNA design with optimal parameter settings and appropriate interpretation of results and present a brief overview of CRISPR-Cas9 applications,such as genetic improvement and sustainability in *** discuss challenging issues,particularly in the context of computational biology,in the use of computational tools in CRISPR-based genome *** review provides a synthesis of bioinformatics tools used for CRISPR-Cas9 sgRNA design and outcome assessment and offers a general view of CRISPR-based applications in farmed fish,which are expected to facilitate genome editing programs and hence improve aquaculture breeding,production,and sustainability.

关键词： CRISPR-Cas9 Genome editing sgRNA design Outcome assessment bioinformatics tools Aquaculture applications

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A Panorama on Selection and Use of bioinformatics tools in the Brazilian University Context 12th

A Panorama on Selection and Use of Bioinformatics Tools in t...

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12th International Conference on Universal Access in Human-Computer Interaction (UAHCI) Held as Part of 20th International Conference on Human-Computer Interaction (HCI International)

作者： Machado Paixao-Cortes, Vanessa Stangherlin Paixao-Cortes, Walter Ritzel Campos, Marcia de Borba de Souza, Osmar Norberto Pontifical Catholic Univ Rio Grande do Sul PUCRS Sch Technol Porto Alegre RS Brazil

ISBN: (纸本)9783319920528;9783319920511

bioinformatics is an interdisciplinary area that uses computational tools to process large amounts of biological data, such as sequence and structures of biological macromolecules, often derived from experimental methods. To manipulate these data and obtain meaningful results, bioinformatics employs a variety of databases and software tools based on complex interfaces, command line tools, task integration, abstract information, and jargons of a specific knowledge domain. Human-computer interaction issues, such as usability, ergonomics, satisfaction of use, and accessibility may hinder the efficient exploration of the multidimensional nature of biological information. In an educational context, these issues constitute barriers to the use of these tools, particularly by visually impaired users. In this artic, we investigate the technological/pedagogical resources used for teaching bioinformatics in the Brazilian context and the perceptions of educators about the inclusion of the visually impaired. A quantitative-qualitative methodology was used for data collection and analysis. The study shows the tools and procedures most commonly used to support the teaching of bioinformatics in Brazilian universities. Also, it reveals that most bioinformatics teachers are not prepared to work with visually impaired students, evidencing the lack of information on assistive/inclusive technologies and/or their use.

关键词： Human-Computer Interaction bioinformatics tools bioinformatics teaching Visually impaired users

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Human Factors in the Design and Evaluation of bioinformatics tools

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Procedia Manufacturing 2015年 3卷 2003-2010页

作者： Al-Ageel, Naelah Al-Wabil, Areej Badr, Ghada AlOmar, Noura Software Engineering Department College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Computer Science Department College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia

Human factors contribute significantly to the information visualization design considerations and usability evaluation process, and have been shown to play an important role in the design, development and quality assurance of bioinformatics tools. Despite the technological advances in bioinformatics computational methods, humans are an indispensable part of the data mining and decision making process. The complexity of biology data visualization can make perception and analysis a complex cognitive activity for professionals in the bioinformatics domain. Information Visualization (InfoVis) can provide valuable assistance for data analysis in bioinformatics by visually depicting sequences, genomes, alignments, and macromolecular structures. InfoVis coupled with interaction modalities of bioinformatics tools also impact the efficiency and effectiveness of decision-making tasks in applied bioinformatics computing. However, the way people perceive and interact with bioinformatics tools can strongly influence their understanding of the complex data as well as the perceived usability and accessibility of these systems. In this paper, we present a synthesis of research studies and initiatives that have recently examined human factors in interaction and visualization for bioinformatics tools, particularly in perception-based design. Although bioinformatics’ visualization and interaction design research that involves human factors is considered in its infancy, a plethora of potentially promising areas have yet to be explored. The aims of this paper are to review current human factors research in interaction, usability and visualization within bioinformatics tools to provide a basis for future investigations in systems and software engineering of bioinformatics tools, and to identify promising areas for future research directions in interaction design of bioinformatics tools. © 2015 The Authors

关键词： bioinformatics tools Heuristics evaluation Human factors Usability metrics

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bioinformatics tools for quantitative and functional metagenome and metatranscriptome data analysis in microbes (vol 19, 2017)

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BRIEFINGS IN bioinformatics 2018年第2期19卷 360-360页

作者： Niu, Sheng-Yong Yang, Jinyu McDermaid, Adam Zhao, Jing Kang, Yu Ma, Qin Department of Biochemical Science and Technology National Taiwan University Taiwan Department of Mathematics and Statistics at South Dakota State University Brookings SD USA Department of Mathematics and Statistics at South Dakota State University Brookings SD USA Department of Internal Medicine at University of South Dakota Sanford School of Medicine Beijing Institute of Genomics of Chinese Academy of Sciences Department of Mathematics and Statistics at South Dakota State University and BioSNTR SD USA Corresponding author: Qin Ma Bioinformatics and Mathematical Biosciences Lab Department of Agronomy Horticulture and Plant Science South Dakota State University Brookings SD 57006 USA. Tel.: 1-706-254-4293 E-mail: qin.ma@sdstate.edu

Metagenomic and metatranscriptomic sequencing approaches are more frequently being used to link microbiota to important diseases and ecological changes. Many analyses have been used to compare the taxonomic and functional profiles of microbiota across habitats or individuals. While a large portion of metagenomic analyses focus on species-level profiling, some studies use strain-level metagenomic analyses to investigate the relationship between specific strains and certain circumstances. Metatranscriptomic analysis provides another important insight into activities of genes by examining gene expression levels of microbiota. Hence, combining metagenomic and metatranscriptomic analyses will help understand the activity or enrichment of a given gene set, such as drug-resistant genes among microbiome samples. Here, we summarize existing bioinformatics tools of metagenomic and metatranscriptomic data analysis, the purpose of which is to assist researchers in deciding the appropriate tools for their microbiome studies. Additionally, we propose an Integrated Meta-Function mapping pipeline to incorporate various reference databases and accelerate functional gene mapping procedures for both metagenomic and metatranscriptomic analyses.

关键词： metagenome metatranscriptome microbe bioinformatics tools functional and quantitative analysis integrated mapping pipeline

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