Advances in Bioinformatics

The dynamics of human metabolism and physiology is governed by the complex microbial communities present in different body sites. Advances in sequencing technologies and computational methods have boosted the microbiome analysis towards better resolution. Presently, microbiome research field has bloomed with generation of massive datasets and development of huge number of analysis tools. However, the complexity of the workflows and diversity of the tools in the repertoires make the field difficult. In this chapter we systematically discuss the metataxonomics, metagenomics and metatranscriptomics approaches, pipelines and the recommended tools. Further, the state-of-the-art downstream analysis techniques and visualisation tools were discussed. This chapter will help the researchers in computational analysis considering their biological questions related to human microbiome.

Abhirupa Ghosh

Shazia Firdous

Sudipto Saha

Bioinformatics for Human Microbiome

人类微生物组生物信息学

Metabolomics is a comprehensive and systematic determination of different metabolite levels, their interactions and dynamics from the complete set of small molecule called metabolome in any biological system. Metabolome is the complete set of metabolite present in any organism. Thousands of metabolites may be present in any animal or plant metabolome. Extracting biological information from a large metabolomics dataset is a big challenge in the field of metabolomics. Sample preparation and its classification, identification, and estimation of the quantity of individual metabolite, etc. are some of the important challenges. Rapid improvements in Nuclear Magnetic Resonance (NMR)-based methods, Mass Spectroscopy (MS), computer software and hardware which can handle large dataset leads to the development of high-throughput metabolomics methods. The pipeline for metabolomics data processing is discussed in this chapter.

Priya Ranjan Kumar

Santosh Kumar Mishra

Sarika Srivastava

Computational Metabolomics

计算代谢组学

Bioinformatics emerged as a new interdisciplinary science that provides an excellent way to understand biological sciences. It contains various biological databases such as nucleic acids, proteins, structures, pathways, interactions, etc. In addition, it also a comprehensive source of different softwares and tools. In silico approaches are very much helpful to do curation and annotation of various types of biological data. Due to advancement in DNA sequencing technology such as from Sanger methods to next generation sequencing (NGS), second generation and third generation played a significant role to generate enormous biological data. These biological data are being deposited in the various databases for further analysis and use. A small untranslated RNA molecule like microRNA (miRNA) plays a vital role in the regulation of the different biological processes. This chapter highlights different miRNA databases and mircoRNA prediction tools such as psRNATarget, RNAhybrid, miRscan, miRanda, TargetScan, PicTar, and Diana-MicroT, which are being utilized to mechanistically analysis of miRNA.

Indra Mani

Role of Bioinformatics in MicroRNA Analysis

生物信息学在微RNA分析中的作用

Bioinformatics is an emerging area of science because technological advances in the field of life sciences have led to the generation of increasingly accumulating large volumes of biological data. The large size of such data will create a huge amount of value but presents numerous challenges of storage, annotation, and curation at the same time. Bioinformatics has allowed the handling of such a large amount of data and has thus paved the way for the rise of "omics" technologies. This chapter focuses on the role of bioinformatics in major "omics" fields, namely genomics, transcriptomics, proteomics, and metabolomics and also highlights upcoming fields like nutrigenomics, chemoinformatics, molecular phylogenetics, systems and synthetic biology, which have progressed due to the beautiful amalgamation of information technology, mathematics, chemistry, and omics sciences. The diverse research areas of bioinformatics like the development of biological databases, genome analysis, 3D structure prediction, drug discovery, clinical applications as well as mathematical modeling of metabolic processes have also been discussed in this chapter.

Disha Gangotia

Aeshna Gupta

Role of Bioinformatics in Biological Sciences

生物信息学在生物科学中的作用

In the past few decades, bioinformatics has been extensively explored in many areas of biological sciences. It combines the principles of biology, computer science, mathematics, physics, and statistics to analyze and interpret biological data. It uses computation power, algorithm and software for extracting knowledge from biological data for analysis, prediction, imaging, and visualization purpose. In this chapter, we highlight recent developments in this field and how the potential of bioinformatics has harnessed in multiple disciplines.

Henny Patel

Dhruti Bhatt

Shreya Shakhreliya

Navya L. Lam

Rupesh Maurya

Vijai Singh

An Introduction and Applications of Bioinformatics

生物信息学简介与应用

Bioinformatics has emerged as a vital component of almost all the fields of biological sciences. Its ability to quickly generate, analyze, and interpret large amounts of data has enabled researchers to integrate it into drug discovery and development. The traditional process of drug discovery had its limitations including increased time consumption and cost, low success rates, inaccurate drug target selection, regulatory and ethical concerns, and lack of personalization. To overcome these challenges, bioinformatics has gained much interest in different stages of drug discovery. In this chapter, we summarize the role of bioinformatics in the high-throughput drug screening process involving both ligand-based and structure-based screening strategies. The most prominent advantage it offers is the ability to handle large amounts of data within seconds to minutes. This chapter also provides a brief account of various bioinformatics tools and databases which have a prominent role in the drug screening process. Although bioinformatics has been proven beneficial, it still has some limitations in terms of the complexity of data that is handled. With the advent of artificial intelligence and machine learning, it is expected that it would definitely strengthen the biomedical field.

Tanya Waseem

Mustafeez Mujtaba Babar

Gholamreza Abdi

Jayakumar Rajadas

Use of Bioinformatics in High-Throughput Drug Screening

生物信息学在高通量药物筛选中的应用

In today's healthcare industry, we prefer methods that are highly effective and minimize risks. Precision medicine is a new field that utilizes algorithms in bioinformatics to provide precise treatment for individuals. Bioinformatics tools not only assist doctors find the most appropriate therapeutic solutions for each patient but also aid in uncovering vast amounts of life science and clinical data for healthcare development. Scientists have found that single nucleotide polymorphism is the primary agent of genetic modification and a potential tool for genetic mapping. Bioinformatics tools combine genetic information with phenotypes and drug responses to help doctors choose the most appropriate treatment for a patient. In addition, algorithms in bioinformatics also help doctors reduce their workload, both in the field of diagnosis and the field of treatment. Besides, the development of bioinformatics also helps scientists create comparative models of biomolecular sequences or molecular mechanisms and generate medical examination records of patients. By optimizing the treatment method based on the potential of bioinformatics, we can minimize the cost of drugs, medical equipment, and the patient's treatment time.

Mai-Anh Nguyen

Chia-Ching Wu

Dinh-Toi Chu

Bioinformatics in Precision Medicine and Healthcare

精准医学与医疗保健中的生物信息学

Bioinformatics plays a crucial role in advancing genome editing techniques by utilizing computational tools and algorithms to analyze biological data. This chapter provides an overview of the role of bioinformatics in genome editing, focusing on key areas where it is applied. These areas include computational analysis of target sequences, prediction, and evaluation of off-target effects, designing and optimizing CRISPR systems, functional annotation of genomic variants, comparative genomics, homology analysis, and integration of multi-omics data. By leveraging bioinformatics, researchers can identify target sites for gene editing, predict and minimize off-target effects, enhance the efficiency of CRISPR systems, understand the functional consequences of genetic alterations, explore evolutionary relationships, and gain comprehensive insights into biological systems. Moreover, comparative genomics and homology analysis are discussed as vital approaches that leverage bioinformatics to understand evolutionary relationships and identify conserved elements across species. Integration of multi-omics data, such as genomics, transcriptomics, and proteomics, is highlighted as a powerful strategy for gaining comprehensive insights into biological systems. While challenges exist, such as accurate off-target prediction and data management, future directions involving machine learning and user-friendly tools hold promise. Bioinformatics continues to revolutionize genome editing, advancing precision medicine, agriculture, and biological research.

Amit Joshi

Ajay Kumar

Vikas Kaushik

Prashant Kumar

Sushma Dubey

Role of Bioinformatics in Genome Editing

生物信息学在基因编辑中的作用

Structural bioinformatics is a captivating discipline that delves into the intricate realm related to proteins, RNA, and DNA, the macromolecules of life. Its primary focus lies in comprehending and foreseeing the enigmatic three-dimensional (3D) architecture of these fundamental entities. By employing cutting-edge computational techniques and advanced algorithms, structural bioinformatics unravels the complex interplay between structure and function, shedding light on the inner workings of life's molecular machinery. Bioinformatics is an interdisciplinary field that combines experimental and computational approaches to investigate various aspects of macromolecular 3D structure. By utilizing experimentally determined structures and computational models, bioinformatics aims to explore diverse inquiries related to macromolecules. These inquiries encompass understanding the distinctions and similarities between macro and micro structures, understanding the rules of molecular interaction, evolution, and folding, and revealing the complexity of structure-function correlations. Structural bioinformatics, a specialized domain within the realm of computational structural biology, encompasses the study and analysis of biological structures. The term "structural" in this context aligns with its definition in the field of structural biology. The field of structural bioinformatics is dedicated to addressing biological challenges and unveiling novel insights through the development of innovative methodologies for the analysis of data pertaining to biological macromolecules.

Juveriya Israr

Shabroz Alam

Sahabjada Siddiqui

Sankalp Misra

Indrajeet Singh

Advances in Structural Bioinformatics

结构生物信息学进展

Next-generation sequencing (NGS) technologies have revolutionized the field of genomics by enabling high-throughput, cost-effective, and rapid DNA sequencing on an unprecedented scale. This introduction offers a synopsis of NGS and its profound implications across diverse areas of biological research and medical diagnostics. The fundamental principles underlying NGS, including library preparation, sequencing-by-synthesis, and data generation, are outlined. The different NGS platforms, such as Illumina, Ion Torrent, and Oxford Nanopore, as well as their respective strengths and limitations, are discussed. Recent advancements in sequencing technologies, such as single-cell sequencing, long-read sequencing, and spatial transcriptomics, are explored, expanding the capabilities of NGS and facilitating comprehensive genomic investigations. Subsequently, the applications of NGS in genomics, transcriptomics, epigenomics, metagenomics, and personalized medicine are examined. The accelerated discovery of genetic variants, gene expression patterns, DNA methylation profiles, and microbial communities through NGS is emphasized. Moreover, the role of NGS in uncovering disease mechanisms, identifying therapeutic targets, and enabling precision medicine approaches is discussed. Furthermore, the computational challenges associated with NGS data analysis, including read alignment, variant calling, and data interpretation, are addressed. The pivotal role of bioinformatics and data analysis pipelines in transforming raw sequencing data into biologically meaningful insights is highlighted. Additionally, the integration of NGS data with other omics datasets and the emerging field of multi-omics integration, providing a holistic view of biological systems, are briefly touched upon. Additionally, the impact of NGS on clinical diagnostics, encompassing the detection of genetic disorders, cancer genomics, infectious disease surveillance, and pharmacogenomics, is elucidated. The potential of NGS-based liquid biopsies and non-invasive prenatal testing in revolutionizing clinical practice is underscored. Lastly, the challenges and considerations associated with NGS, such as data storage, privacy concerns, ethical considerations, and the importance of standardization and quality control measures, are addressed. The significance of interdisciplinary collaborations among scientists, clinicians, and bioinformaticians in harnessing the full potential of NGS and driving innovation in genomic research and healthcare is emphasized. In conclusion, this comprehensive introduction to next-generation sequencing provides an overview of the technology, its applications, and its impact across various fields. By empowering researchers and clinicians with unprecedented genomic information, NGS has the potential to revolutionize our understanding of biological systems, unravel disease complexities, and facilitate personalized approaches to healthcare.

ISSN	1687-8027, 1687-8035
h-index	26

Publication Information	Publisher: Hindawi Limited，Publishing cycle: ，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 2010，Proportion of original research papers: 0.00%，Self Citation Rate:N.A.， Gold OA Rate: 0.00%

Advances in Bioinformatics

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