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BIOINFORMATICS - AN INTRODUCTION

Topics to be Covered
    1. Motivation for Studying Bioinfomatics
    2. Introduction to Bioinformatics
    3. Difference b/w Bioinformatics and Computational Biology
    4. Goals of Bioinformatics
    5. Branches of Bioinformatics
    6. Aim of Bioinformatics
    7. Applications of Bioinformatics
    8. Various Research areas of Bioinformatics
    9. Available Bioinformatics Resources on web
    10. Limitations of Bioinformatics

Motivation for Studying Bioinformatics

It is important to know that many of you haven’t heard of Bioinformatics before graduating. Bioinformatics is an interesting discipline in the era of computer’s and technology.

So now let us understand the concept about, why do we study Bioinformatics & why it is important.

    • Since day by day biological experiments are being conducted at an enormous rate
    • Due to this, massive amount of biological data is being produced at very high rate.
    • So Managing and Interpreting this biological data was becoming a great challenge for biologists working in multiple domains.
    • For managing all these biological data, scientists, researchers and experts started using machines / computers.
    • Hence by the use of multiple technology, these experts were able to gather, analyze and Integrate all these biological information at a particular place.
    • This results in proper organization, and management of data at a particular place
    • And finally Biological databases started emerging at an extensive rate which further results in the discovery of an interesting domain namely Bioinformatics.
    • These stored biological knowledge was further used in medical diagnosis, researches and to answer multiple biological problems which ultimately lead to gain the interest in this desired domain. 

Click below to watch this complete lecture on YouTube

Introduction to Bioinformatics

      • Bioinformatics is like an amoeba because it has no clear cut boundaries. Which means that this discipline does not have clear cut definition.
      • Definition 1 : It is an Interdisciplinary area of research, which is an Integration of Biology, Computer sciences, Mathematics, Statistics, Physics, Chemistry, Biological Sciences etc.
      • Definition 2: Bioinformatics is an application of computational and analytical tools which helps in capturing and Interpreting biological data. (Ghosh & Mallick)
      • Definition 3 : An interdisciplinary area of research between computer science and biological sciences. (Jin Xiong)
      • Definition 4 : A union of biology and informatics, which means that Bioinformatics involves the technology that uses computers for storage, retrieval, manipulation, and distribution of information associated with biological objects such as DNA, RNA and proteins. (Luscombe et al.)
      • Bioinformatics is usually geared up by major sequencing projects
      • Focus areas of bioinformatics is generally working with biologically oriented data such as Nucleic acid  & Protein sequences, structures, pathway, interactions, drug design etc.

      • This domain of science mostly used for two reasons namely :
        • Organizing and storing data into biological databases
        • Development of tools which can further derive more information from these stored biological data.
      • Bioinformatics can be seen as an integral component in variety of fields such as : Functional genomics, biomolecular structure, proteome analysis, cell metabolism, biodiversity, chemical engineering, drug design etc.
      • One of the main feature of bioinformatics is that, it is capable of giving in silico answers to certain biological problems.  
      • It is important to note that Bioinformatics is completely different from computational biology in the sense that it is only limited to sequence, structural and functional analysis of genes & genomes and their associated products, while on the other hand computational biology focuses all the areas of biology where the computation is involved.

Click below to watch this complete lecture on YouTube

Difference between Bioinformatics and Computational biology.
Bioinformatics 
    •  Focus on data analysis
    • Mostly associated with analyzing large datasets
    • Researchers in this domain have indepth knowledge of Computer science, statistics, mathematics or Biology.
    • Working tools include Sequence alignment algorithms, Machine learning, Network analysis tools.
    • Includes wide range of biological research applications from genetic studies to drug designing.
    • Main field of study includes Genomics, Proteomics and Drug design.
    • More concerned with development and application of computational methods for analyzing and interpretation of large biological datasets.
Computational Biology
    • Focus on Modeling and Simulation.
    • Mostly associated with simulating and modeling of complex biological systems.
    • Researchers in this domain have strong knowledge of Mathematics and Physics.
    • Working tools include MD simulations, Monte carlo methods, Agent based modelling.
    • Includes wide range of biolgical research applications from Protein folding to gene regulation & cell signalling pathways.
    • Main field of study includes Systems biology research.
    • More concerned with development and application of mathematical modeling and Simulation for the study of biological systems.
Goals of Bioinformatics
    • Ultimate Goal is to better understand living system and how it works at molecular level.

    • To analyze raw biological data (molecular sequence & structural data) to generate new insights and provide global perspective of cell.

    • Solving biological problems using sequences (Proteins & Nucleotides).

Click below to watch this complete lecture on YouTube

Branches of Bioinformatics

it is important to know that the flow of information at molecular level is maily associated with Central Dogma of biology where DNA is transcribed into RNA and further RNA is translated into proteins. Hence these three components namely DNA, RNA and proteins are also referred to as molecules of life.

Some of the branches of bioinformatics are namely :

1. Genomics

        • Definition : A Molecular biology branch that is associated with structure, function, Evolution and mapping of genomes.
        • Involved in determination and mapping on Genome.
        • Databases associated with Genomics are namely RefSeq (Reference Sequence), GDB (Genome Data Viewer), GEO (Gene Expression Omnibus), GenBank, dbGaP (Database of Genotypes and Phenotypes), dbVar (Database of Genomics Structural Variation), dbSNP (Database of Single Nucleotide Polymorphisms), Gene etc.

2. Transcriptomics

        • Definition : study of Transcriptome (whole set of mRNA molecules in one or more population of biological cells)
        • Involved in the prediction of gene expression level using techniques such as DNA Microarrays.
        • Databases associated with Transcriptomics are namely : Generic gene expression databases, Microarray gene expression databases etc.

3. Proteomics

        • Definition : study of Proteomes and their functions.
        • Usually associated with sequencing of amino acids, structure determination, and functions of proteins.
        • Databases associated with Proteomics are namely : UniProt, neXtProt, Protopedia, Protein Data Bank, Human Protein Atlas, STRING, SuperPose, TopFIND etc.

4. Systems Biology

        • Definition : Study of molecular structure and dynamics of biological macromolecules.
        • Associated with the aid of mathematical modelling, simulation and data analysis and is involved in the generation of experimentally predictive models.
        • Database & Tools associated with Systems Biology are namely : Pathway analysis, Modelling & Simulation using CellDesigner | Gene ontology & DAVID (Database for Annotation, Visualization & Integrated Discovery) Analysis etc.

5. Structural Bioinformatics

        • Definition : Domain of bioinformatics dealing with analysis and prediction of 3D structure of biological macromolecules such as Proteins, RNA and DNA.
        • Involve in Protein structure prediction, drug designing, QSAR (Quantitative Structure Activity Relationship)
        • Databases of Structural bioinformatics are namely : PDB (Protein Data Bank), SCOP (Structural Classification of Proteins), CATH (Class Architecture Topography Homology), Drug Design – Autodock vina etc.

6. Functional Genomics

        • Study of Genes, and their resulting proteins also role played by the proteins.
        • Aims in determination of functions of multiple genes.
        • Databases of Functional Genomics are namely Array Express, Expression Atlas etc.

7. Metabolomics 

        • Definitions : large scale study of metabolites (Small molecules) within biological systems.
        • High throughput measurement of hundreds to thousands of metabolites at a time from multiple sample at once.
        • Databases associated with metabolomics are namely : Human Metabolome database, MetaCyc, REACTOME, PubChem, Birmingham Metabolite Library, KEGG (Kyoto Encyclopedia of genes and genomes), MetaboLights, METLIN, LipidCreater, BioDendro etc.

8. Chemoinformatics

        • Definition : Domain of bioinformatics which is involved in solving chemical problems using computers.
        • Involved in manipulations in 2D and 3D structure of chemical compounds, Drug Designing, representation of chemical information etc.
        • Databases associated with Chemoinformatics are namely : ZINC, PubChem, ChEMBL, DrugBank etc.

9. Phylogeny

        • Definition : Representation of the relationship and evolutionary history of an organism
        • Important in the field of taxonomy or sometimes called systematics for classifying and naming the organism.
        • Tools for Phylogeny are namely : PHYLIP, MEGA, Clustal Omega etc.

Click below to watch this complete lecture on YouTube

Aim of Bioinformatics:

Bioinformatics can be used in multiple aspects. Some of them are listed namely Data Acquisition, Tools & Database Management, Data Analysis, Data Integration, Structural Biology, Functional Annotation, Systems Biology, Phylogenetics, Drug Discovery, Personalized Medicine etc.

        1. Data Acquisition
          • Generally associated with the 
        2. Tools and Database Management
        3. Data Analysis
        4. Data Integration
        5. Structural Biology
        6. Functional Annotation
        7. Systems Biology
        8. Phylogenetics
          •  
        9. Drug Discovery
          • Associated with discovering drug candidate via computational methods of screening compounds.
        10. Personalized Medicine
          • Associated with studying an Individual Genomic variations for developing medical treatments to specific patients which will result in improving efficacy and minimizing adverse health effects.
Applications of Bioinformatics

As we all know that Bioinformatics is a vast domain and is mainly associated with multiple applications such as Structure analysis, Sequence analysis and Function analysis. Now let us understand each of them briefly :

Structure Analysis : Includes the tasks that are performed with protein structure.

Sequence Analysis : Includes the tasks that are performed using Protein & Nucleotide sequences.

Function Analysis : Includes the tasks that are performed using protein sequences, nucleotide sequences and protein structures.

Function Analysis

Modeling of Metabolic pathway

Profiling of gene expression

Protein interaction prediction

Prediction of protein subcellular localization.

Structure Analysis

Prediction of Nucleic acid structure

Prediction of Protein Structure

Classification of Protein structure

Protein Structure – Structure comparision.

Sequence Analysis

Genome Comparision & Phylogeny

Prediction of Gene and Promoter 

Motif discovery & Sequence database searching

Sequence alignment.

Various Research areas of Bioinformatics

Since we all know that Bioinformatics is an interdisciplinary area of research which can be applied to several fields such as sequence analysis, structure prediction, mathematical modelling of biological objects, database construction & management, drug discovery, research & development etc.

Now let us understand each of these areas briefly :

    1. Sequence Analysis can be applied to find sequence homologues of a gene and to look for similar genes in other organisms. 
    2. Structure Prediction
    3. Mathematical Modelling of biological objects
    4. Database construction & its Management
    5. Drug Discovery
    6. Research & Development
Available Bioinformatics Resources on Web

To be updated……

Limitations of Bioinformatics

To be updated……

Sources :
    • Bioinformatics (Principles and Applications) by Zhumur Ghosh and Bibekanand Mallick, 
    • Essential bioinformatics by Jin Xiong (Texas A&M University)
    • Pluto bioinformatics
    • G Academy Notes 
    • https://www.uab.edu/cb2/research-menus/structural-bioinformatics-research
    • https://en.wikipedia.org/wiki/List_of_biological_databases
    • https://researchguides.ben.edu/c.php?g=978382&p=7121726
    • European Molecular Biology Laboratory – European Bioinformatics Institute
    • What is Phylogeny? – News-Medical.Net
Content edited and updated by Avtar Kishan
B.Sc. Biochemistry, M.Sc. Bioinformatics

Co-founder of G Academy
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