Bioinformatics: promises and progress

Bioinformatics is a multidisciplinary science that solves and analyzes biological problems. With the quantum explosion in biomedical data, the demand of bioinformatics has increased gradually. Present paper provides an overview of various ways through which the biologists or biological researchers in the domain of neurology, structural and functional biology, evolutionary biology, clinical science, etc., use bioinformatics applications for data analysis to summarise their research. A new perspective is used to classify the knowledge available in the field thus will help general audience to understand the application of bioinformatics.

[1]  Casey M. Bergman,et al.  Evolutionary Genomics of Transposable Elements in Saccharomyces cerevisiae , 2012, PloS one.

[2]  P. Kumar,et al.  Metabolomics in agriculture. , 2012, Omics : a journal of integrative biology.

[3]  Megha Agrawal,et al.  Meta analysis of gene expression changes upon treatment of A549 cells with anti-cancer drugs to identify universal responses , 2012, Comput. Biol. Medicine.

[4]  Panteleeva Ga.  Paraneoplastic bullous dermatoses , 1990 .

[5]  D. Roos,et al.  Bioinformatics--Trying to Swim in a Sea of Data , 2001, Science.

[6]  Olivier Michielin,et al.  Defining and searching for structural motifs using DeepView/Swiss-PdbViewer , 2012, BMC Bioinformatics.

[7]  Christos A. Ouzounis,et al.  The Emergence of Bioinformatics: Historical Perspective, Quick Overview and Future Trends , 2009 .

[8]  T I Oprea,et al.  Cheminformatics: a tool for decision-makers in drug discovery. , 2001, Current opinion in drug discovery & development.

[9]  Gabriele Ausiello,et al.  Structural motifs recurring in different folds recognize the same ligand fragments , 2009, BMC Bioinformatics.

[10]  M. Baker.  Functional genomics: The changes that count , 2012, Nature.

[11]  I. Bernstein,et al.  Biomedical informatics as support to individual healthcare in hereditary colon cancer: the Danish HNPCC system , 2011, Human mutation.

[12]  Victor Maojo,et al.  Viewpoint Paper: Bioinformatics and Medical Informatics: Collaborations on the Road to Genomic Medicine? , 2003, J. Am. Medical Informatics Assoc..

[13]  Athanasia Pavlopoulou,et al.  Unraveling microalgal molecular interactions using evolutionary and structural bioinformatics. , 2013, Gene.

[14]  A. Beauvais,et al.  The diverse applications of RNA‐seq for functional genomic studies in Aspergillus fumigatus , 2012, Annals of the New York Academy of Sciences.

[15]  Lingchong You,et al.  Toward computational systems biology , 2007, Cell Biochemistry and Biophysics.

[16]  Ulla Ruotsalainen,et al.  Neuroinformatics: the integration of shared databases and tools towards integrative neuroscience. , 2002, Journal of integrative neuroscience.

[17]  Catherine L. Worth,et al.  Structural biology and bioinformatics in drug design: opportunities and challenges for target identification and lead discovery , 2006, Philosophical Transactions of the Royal Society B: Biological Sciences.

[18]  Shipra Gupta,et al.  Prediction of a new surface binding pocket and evaluation of inhibitors against huntingtin interacting protein 14: an insight using docking studies , 2011, Journal of molecular modeling.

[19]  Vladimir Brusic,et al.  Immunoinformatics--the new kid in town. , 2003, Novartis Foundation symposium.

[20]  T Reichhardt,et al.  It's sink or swim as a tidal wave of data approaches , 1999, Nature.

[21]  Christina Backes,et al.  miRTrail - a comprehensive webserver for analyzing gene and miRNA patterns to enhance the understanding of regulatory mechanisms in diseases , 2012, BMC Bioinformatics.

[22]  Michael B. Stadler,et al.  Confero: an integrated contrast data and gene set platform for computational analysis and biological interpretation of omics data , 2013, BMC Genomics.

[23]  Akira R. Kinjo,et al.  Composite Structural Motifs of Binding Sites for Delineating Biological Functions of Proteins , 2011, PloS one.

[24]  Ronald C. Petersen,et al.  Identification of Altered Metabolic Pathways in Plasma and CSF in Mild Cognitive Impairment and Alzheimer’s Disease Using Metabolomics , 2013, PloS one.

[25]  J. Snoeyink,et al.  Distance-based identification of structure motifs in proteins using constrained frequent subgraph mining. , 2006, Computational systems bioinformatics. Computational Systems Bioinformatics Conference.

[26]  A. Blomström.  Viral metagenomics as an emerging and powerful tool in veterinary medicine , 2011, The Veterinary quarterly.

[27]  C. Lim,et al.  Discovering structural motifs using a structural alphabet: Application to magnesium-binding sites , 2007, BMC Bioinformatics.