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Review Article | Open Access
  • Available online freely | Peer Reviewed
  • The Emerging Role of Bioinformatics in Biotechnology

    Nida Tabassum Khan 1      

    1Department of Biotechnology, Faculty of Life Sciences and Informatics, Balochistan University of Information Technology Engineering and Management Sciences,(BUITEMS),Quetta, Pakistan


    Bioinformatic tools is widely used to manage the enormous genomic and proteomic data involving DNA/protein sequences management, drug designing, homology modelling, motif/domain prediction ,docking, annotation and dynamic simulation etc. Bioinformatics offers a wide range of applications in numerous disciplines such as genomics. Proteomics, comparative genomics, nutrigenomics, microbial genome, biodefense, forensics etc. Thus it offers promising future to accelerate scientific research in biotechnology

    Received 18 Jun 2018; Accepted 02 Aug 2018; Published 07 Aug 2018;

    Academic Editor:Hammad Afzal, SZABIST, Karachi.

    Checked for plagiarism: Yes

    Review by: Single-blind

    Copyright©  2018 Nida Tabassum Khan

    Creative Commons License    This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

    Competing interests

    The authors have declared that no competing interests exist.


    Nida Tabassum Khan (2018) The Emerging Role of Bioinformatics in Biotechnology. Journal of Biotechnology and Biomedical Science - 1(3):13-24.
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    Bioinformatics provided computational ways for data analysis by employing informatics tools and softwares to determine protein/gene structure or sequence, homology, molecular modeling of biological system, molecular docking etc to analyze and interpret data in insilico 1.Currently bioinformatics have become a principal technology in all life sciences research. Bioinformatics has been integrated into a number of different disciplines where it assists in better understanding of the data in a shorter time frame 2. With the massive advancement in information technology, bioinformatics is growing rapidly providing new ways and approaches for the assessment of valuable data 3.Data mining and manipulations is an important aspect of bioinformatic 4. It allows researchers to collect, store, catalogue and analyse information in unique format that is easily manipulated for future research 5. Some examples of data manipulation include molecular online tools and the bio extract server 6. It is useful for accessing bimolecular data from many sources for many purposes. This is lab template for the proper accession and usage of online molecular tools like bio extract 7.

    Some applications of bioinformatics in biotechnology is given below:


    To manage an escalating amount of genomic information, bioinformatic tools are required to maintain and analyze the DNA sequences from different organism 8. Determination of sequence homology, gene finding, coding region identification, structural and functional analyses of genomic sequences etc, all this is possible by the use of different bioinformatics tools and software packages 9.

    Given below is a list of few bioinformatics tools used in genomics Table 1.

    Table 1. Bioinformatics tools/databases used in Genomics
    Bioinformatics tools Purpose
    Carrie Transcriptional regulatory networks database 10
    CisML Motif detection tool 11
    ICSF Identification of conserved structural features in TF binding sites 12
    Possum  Tool for motif searching 13
    Promoser Promoter extraction tool from eukaryotic organisms 14
    REPFIND Determine clustered repeats in DNA fragment 15
    Cluster‐Buster Tool for predicting motifs cluster in DNA sequences 16
    Cister Finds regulatory regions in DNA fragments 17
    Clover Find overrepresented motifs in DNA sequences 18
    GLAM Tool for predicting functional motifs 19, 20
    MotifViz Identification of overrepresented motifs 21
    RANKGENE Tool for analysing gene expression data 22
    ROVER Predicts overrepresented motifs in DNA fragments 23
    SeqVISTA Sequences viewer tool 24
    Tractor Tool to find transcription factors with over‐represented binding sites in the upstream regions of co‐expressed human genes 25
    OHMICS Oral human microbiome integrated computational system 26

    Comparative Genomics

    Bioinformatics plays an important role in comparative genomics by determing the genomic structural and functional relationship between different biological species 27.

    Given below is a list of few bioinformatics tools used in comparative genomics Table 2.

    Table 2. Bioinformatics tools/databases used in Comparative genomics
    Bioinformatics tools Purpose
    BLAST DNA or protein sequence alignment tool 28
    HMMER Homologous protein sequences searching tool 29
    Clustal Omega Multiple sequence alignments tool 30
    Sequerome Sequence profiling tool 31
    ProtParam Predicts the physico-chemical properties of proteins 32
    novoSNP Predicts single point mutation in DNA sequences 33
    ORF Finder Find open reading frame in putative genes 34, 35
    Virtual Foorprint Analysis of whole prokaryotic genome 36
    WebGeSTer Predicts gene termination sites during transcription 37
    Genscan Find exon-intron sites in DNA sequences 38
    Softberry Tools Genomes annotation tool along with the structure and function prediction of biological molecules 39
    MEGA Study evolutionary relationship 40
    MOLPHY Maximum likelihood based phylogenetic analysis tool 41
    PHYLIP Tool for phylogenetic studies 42
    JStree Tool for viewing and editing phylogenetic trees 43
    Jalview It is an alignment editing tool 44
    DNA Data Bank of Japan Resources for nucleotide sequences 45
    Rfam Database contains collection of RNA families 46
    Uniprot Protein sequence database47
    Protein Data Bank Database provide data on structures of nucleic acids, proteins etc 48
    SWISS PROT Database containing the manually annotated protein sequences 49
    InterPro Provide information on protein families, its conserved domains and actives sites 50
    Proteomics Identifications Database Contains data on functional characterization and post-translation modification of proteins and peptides 51
    Ensembl Database containing annotated genomes of eukaryotes including human, mouse and other vertebrates 52
    Medherb Database for medicinally herbs 53


    Advanced molecular based techniques led to the accumulation of huge proteomic data of protein activity patterns, interactions, profiling, composition, structural information, image analysis, peptide mass fingerprinting, peptide fragmentation fingerprinting etc 54, 55. This enormous data could be managed by using different tools of bioinformatics.

    Given below is a list of few bioinformatics tools used in proteomics Table 3.

    Table 3. Bioinformatics tools/databases used in Proteomics
    Bioinformatics tools Purpose
    K2 / FAST Protein structure alignment tool 56
    SMM Tool for determing peptides binding to major histocompatibility complex 57
    ZDOCK Protein‐protein docking tool 58
    Docking Benchmark Tool to evaluate docking algorithms performance 59
    ZDOCK Server An automated server for running ZDOCK 60 Proteomic analysis for analysing 2D-Gel images 61

    Drug Discovery

    Clinical bioinformatics is an emerging new field of bioinformatics that employs various bioinformatics tool such as computer aided drug designing to design novel drugs, vaccines, DNA drug modelling ,insilico drug testing,etc to produce new and effective drugs in a shorter time frame with lower risks 62, 63.

    Cancer Research and Analysis

    Bioinformatic tools such as NCI 64, NCIP (part of NCI) 65 and CBIIT 66 have played an important role in genomics, proteomics, imaging, and metabolomics to increase our knowledge of the molecular basis of cancer 67.

    Phylogenetic studies

    Using numerous bioinformatics tools, phylogenetic analysis of the molecular data can easily be achieved in a short period of time by constructing phylogenetic trees to study its evolutionary relationship based on sequence alignment 68.

    Forensic Science

    A number of databases consists of DNA profiles of known delinquents 69. Advancement in microarray technology, bayesian networks, programming algorithms etc provides an effective method of evidence organization and interpretation 70, 71.


    Though bioinformatics has limited impact on forensic since there is a need for more advanced algorithms and computational applications so that the established databases may exhibit interoperability with each other 72.


    Progressions in structural /functional genomics and molecular technologies such as genome sequencing and DNA microarrays generates valuable knowledge which explains nutrition in relation of an individual’s genetics which directly influences its metabolism 73. Because of the influx of bioinformatics tools, nutrition-related research is tremendously increased 74, 75.

    Gene Expression

    Regulation of gene expression is the core of functional genomics allowing researchers to apply genomic data to molecular technologies that can quantify the amount of actively transcribing genes in any cell at any time (e.g. gene expression arrays) 76, 77.

    Given below is a list of few bioinformatics tools used in gene expression study Table 4.

    Table 4. Bioinformatics tools/databases used in Gene expression
    Bioinformatics tools Purpose
    GeneChords  Conserved gene retrieval tool 78
    GENEVA Categorizes segmentally altered genes in many complete microbial genomes 79
    HuGE Index Human tissues gene expression database 80
    Inverted Repeats Finder Find inverted repeats in genomic DNA 81
    ORChID Database stores hydroxyl radical cleavage data of DNA sequences 82
    Operons Predicts functional gene clusters 83
    Optimus Retrieve conserved gene cluster data from numerous microbial genomes 84
    Predictome Visualizing tool for bio complexes 85
    Tandem Repeat Database Store information on tandem repeats in genomic DNA 86
    VisANT Tools for visualizing and analysing many biological interactions 87
    BSG Identification of transcription factor binding sites 88
    TFSVM Detection of transcription factor binding site 89

    Food Quality

    New improvements in computing algorithms and available structural simulation databases of recognized structures has brought molecular modeling into conventional food chemistry. Such simulations will make it possible to improve food quality by developing new food additives by comprehending the basis of taste tenacity, antagonism and complementation 90, 91.

    Predicting Protein Structure and Function

    Protein topology prediction is now so much easy thanks to bioinformatics which helps in the prediction of 3D structure of a protein to gain an insight into its function as well 92.

    Given below is a list of few bioinformatics tools used in protein structure and function prediction Table 5.

    Table 5. Bioinformatics tools/databases used in Protein structure and function prediction
    Bioinformatics tools Purpose
    CATH Tool for the categorized organization of proteins 93
    Phyre and Phyre2 Tool for protein structure prediction 94
    HMMSTR For the prediction of sequence-structure correlations in proteins 95
    MODELLER Predicts 3D structure of protein 96
    JPRED/ APSSP2 Predicts secondary structures of proteins 97
    RaptorX Predicts protein structure 98
    PHD Predicts neural network structure 99

    Personalized Medicine

    Doctors will be able to analyse a patient's genetic profile and prescribe the best available drug therapy and dosage from the beginning by employing bioinformatics tool 100.

    Microbial Genome Applications

    Microbes have been studied at very basic level with the help of bioinformatics tools required to analyse their unique set of genes that enables them to survive under unfavourable conditions 101.


    Thus bioinformatics holds significant importance in countless disciplines of biotechnology such as comparative genomics, drug designing, proteomics, molecular modelling, microbial genomics etc


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