Pay Matrix Level-12
No. of Post-01
(UR)
Post – Sr. Scientist
Area Bioinformatics
Age limit : 37 years
PhD in Computational Biology/Bioinformatics with 2 years experience in desired area
Or
ME/M.Tech in Bioinformatics or Genome Informatics or Genetic Engineering with 3 years experience in desired area
Experience of understanding fundamental science behind Artificial Intelligence, machine learning, novel Artificial Intelligence algorithms and architectures, software engineering principles for Artificial Intelligence, natural language processing with proficiency in programming as evident by publications in SCI journals with high impact factor. To be part a group of scientists working in the area of genomics, running the central
bioinformatics facility, developing independent projects and providing bioinformatics support to the user scientists of the Institute.

More at

http://14.139.62.50/CSIR-IITR%20Scientist%20Recruitment%20Adv%202020.pdf

More at http://pandeylab.igm.jhmi.edu/

http://scholar.google.com/citations?user=OhuG0FcAAAAJ&hl=en

More at https://boards.greenhouse.io/twistbioscience/jobs/3135495?gh_src=9ecc0b941us

https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947

Address of the bookmark: https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947

What is Bacterial Comparative Genomics?

Comparative genomics involves the systematic comparison of genomes across different bacterial species or strains. This approach allows scientists to:

• Identify conserved and unique genes.

• Explore genetic determinants of pathogenicity.

• Understand bacterial evolution and phylogenetics.

• Investigate horizontal gene transfer and its role in antibiotic resistance.

Bioinformatics is central to these analyses, enabling the processing and interpretation of large-scale genomic data.

Key Steps in Bacterial Comparative Genomics

1. Genome Sequencing and Assembly: The process begins with obtaining high-quality bacterial genome sequences. Advances in next-generation sequencing (NGS) technologies have made it faster and more affordable to sequence bacterial genomes. Tools such as SPAdes and Velvet are commonly used for genome assembly.

2. Genome Annotation: Annotating a genome involves identifying genes, regulatory elements, and other genomic features. Automated tools like Prokka and RAST provide functional annotations, allowing researchers to predict the roles of genes and proteins.

3. Genome Alignment: Aligning genomes is crucial for identifying conserved regions, single-nucleotide polymorphisms (SNPs), and structural variations. Tools like Mauve and progressiveMauve are commonly employed for whole-genome alignments.

4. Comparative Analyses:

   • Core and Pan-genome Analysis: The core genome consists of genes shared across all strains of a species, while the pan-genome includes all genes found in any strain. Software like Roary and BPGA can perform core and pan-genome analyses.

   • Phylogenetic Analysis: Comparative genomics often involves reconstructing evolutionary relationships. Tools such as MEGA and IQ-TREE facilitate phylogenetic tree construction based on genomic data.

   • Functional Enrichment Analysis: To understand the biological significance of unique or shared genes, functional enrichment analysis using databases like GO (Gene Ontology) and KEGG is essential.

Here are some additional bioinformatics tools that can aid bacterial comparative genomics:

• OrthoFinder: For accurate ortholog identification across multiple genomes.

• PanOCT: Specifically designed for pan-genome clustering and annotation.

• FASTANI: A tool for calculating Average Nucleotide Identity (ANI) for microbial genome comparisons.

• CIRCOS: For visually comparing genomic data through circular genome plots.

• Galaxy Platform: A user-friendly web-based platform offering numerous genomic analysis tools.

• BLAST: Essential for sequence alignment and similarity searches.

• PhyloSift: Focused on phylogenetic analysis of microbial genomes using marker genes.

These tools, in combination with the methods discussed, provide a robust framework for conducting comprehensive comparative genomic studies.

Applications of Bacterial Comparative Genomics

1. Understanding Pathogenicity: Comparative genomics helps identify virulence factors that distinguish pathogenic strains from non-pathogenic relatives. For instance, comparing genomes of Escherichia coli strains has revealed key genetic determinants of pathogenicity in enterohemorrhagic strains.

2. Antibiotic Resistance Research: The spread of antibiotic resistance genes through horizontal gene transfer is a major global concern. Comparative analyses can trace the origins and dissemination of resistance genes, aiding in the development of countermeasures.

3. Microbial Ecology and Evolution: By studying genomic variations, researchers can understand how bacteria adapt to different environments. This is particularly relevant for extremophiles and symbiotic bacteria.

4. Vaccine Development: Identifying conserved antigens across pathogenic strains is critical for vaccine design. Comparative genomics has been instrumental in developing vaccines against pathogens like Neisseria meningitidis.

5. Biotechnology Applications: Comparative studies can uncover unique metabolic pathways in bacteria, paving the way for applications in bioremediation, synthetic biology, and industrial microbiology.

Challenges in Bacterial Comparative Genomics

While the field has made significant strides, several challenges remain:

• Data Overload: The rapid growth of sequencing data requires robust computational infrastructure and efficient algorithms.

• Genome Plasticity: High rates of horizontal gene transfer and genome rearrangements in bacteria complicate comparative analyses.

• Annotation Accuracy: Automated annotation tools are not infallible, and manual curation is often needed for high-confidence results.

• Interpreting Non-Coding Regions: Understanding the functional significance of non-coding genomic regions remains a challenge.

Future Directions

The integration of bacterial comparative genomics with other ‘omics’ approaches—such as transcriptomics, proteomics, and metabolomics—promises a more comprehensive understanding of bacterial biology. Additionally, advancements in machine learning and artificial intelligence are likely to further enhance bioinformatics analyses, enabling the prediction of complex phenotypes from genomic data.

Conclusion

Bacterial comparative genomics, driven by bioinformatics, continues to unravel the complexities of bacterial life. From combating antibiotic resistance to uncovering the secrets of microbial evolution, this interdisciplinary field holds immense potential for addressing pressing challenges in microbiology and beyond. As technology advances, so too will our ability to harness the power of comparative genomics for scientific and societal benefit.

1. Big Data and Bioinformatics

The exponential growth in biological data, driven by advancements in sequencing technologies and high-throughput experiments, has made bioinformatics an indispensable tool. By 2030, we anticipate:

• Petabyte-Scale Data Management: Enhanced storage solutions and cloud computing platforms will allow researchers to handle the vast amounts of data generated from omics studies, including genomics, transcriptomics, and proteomics.

• AI and Machine Learning Integration: Sophisticated algorithms will uncover patterns and relationships in large datasets, enabling predictions about gene function, disease susceptibility, and therapeutic outcomes.

2. Personalized Medicine and Genomics

Bioinformatics will play a pivotal role in tailoring healthcare to individual patients. Key developments include:

• Whole-Genome Sequencing in Clinics: The decreasing cost of sequencing will make it routine in medical diagnostics, enabling personalized treatment plans based on an individual’s genetic makeup.

• Drug Repurposing and Development: Computational tools will identify potential new uses for existing drugs, accelerating the development of targeted therapies.

3. Advancing Computational Tools

The future will see the development of more user-friendly and powerful bioinformatics tools:

• Graph-Based Approaches: Enhanced algorithms for analyzing complex biological networks, such as protein-protein interaction maps.

• Visualization Tools: Intuitive software for visualizing multi-dimensional data, enabling researchers to interpret findings more effectively.

4. Synthetic Biology and Systems Biology

Bioinformatics will continue to drive progress in synthetic and systems biology by:

• Gene Circuit Design: Leveraging computational models to design and simulate synthetic biological systems.

• Understanding Cellular Pathways: Integrating multi-omics data to model cellular processes with unprecedented accuracy.

5. Bioinformatics in Agriculture and Environmental Science

Beyond healthcare, bioinformatics will revolutionize agriculture and environmental conservation:

• Crop Improvement: Genomic studies will help develop high-yield, disease-resistant, and climate-resilient crops.

• Microbial Ecology: Metagenomics will enhance our understanding of microbial communities, aiding in bioremediation and ecosystem management.

6. Democratization of Bioinformatics

Open-source software and accessible education will broaden participation in bioinformatics research:

• Community-Driven Projects: Collaborative platforms like GitHub will continue to foster innovation in tool development.

• Education and Training: Online courses and workshops will bridge skill gaps, enabling researchers from diverse backgrounds to contribute.

Challenges and Ethical Considerations

While the future is bright, challenges remain. Data privacy and ethical concerns surrounding genetic information require careful navigation. Furthermore, addressing the digital divide is critical to ensuring equitable access to bioinformatics resources globally.

Conclusion

The future of bioinformatics is boundless, with opportunities to revolutionize our understanding of life and improve human health. As technologies evolve and collaborations flourish, bioinformatics will undoubtedly remain at the forefront of scientific discovery, unlocking the secrets of life one dataset at a time.

Sequence Analysis and General Bioinformatics

• BLAST, Ian Korf, Mark Yandell, Joseph Bedell, 2003, O'Reilly
• Sequence Analysis in a Nutshell: A Guide to Common Tools and Databases, Scott Markel, Darryl Leon, 2003, O'Reilly
• Bioinformatics for Geneticists, Michael Barnes, Ian C Gray (Editors), 2003, John Wiley & Sons
• Bioinformatics for Dummies, Jean-Michel Claverie, Cedric Notredame, 2003, John Wiley & Sons
• Mathematics of Genome Analysis, Jerome K. Percus, 2002, Cambridge Univ Press
• Bioinformatics Computing, Bryan P. Bergeron, 2002, Prentice Hall
• Evolutionary Computation in Bioinformatics, Gary B. Fogel, David W. Corne (Editors), 2002, Morgan Kaufmann
• Introduction to Bioinformatics, Arthur M. Lesk, 2002, Oxford University Press
• Instant Notes in Bioinformatics, D.R. Westhead, J. H. Parish, R.M. Twyman, 2002, Bios Scientific Pub
• Fundamental Concepts of Bioinformatics, Dan E. Krane, Michael L. Raymer, Michaeel L. Raymer, Elaine Nicpon Marieb, 2002, Benjamin/Cummings
• Essentials of Genomics and Bioinformatics, C. W. Sensen (Editor), 2002, John Wiley & Sons
• Current Topics in Computational Molecular Biology (Computational Molecular Biology), Tao Jiang, Ying Xu, Michael Zhang (Editors), 2002, MIT Press
• Hidden Markov Models for Bioinformatics, Timo Koski, Timo Koskinen, 2001, Kluwer Academic Publishers
• Bioinformatics: From Genomes to Drugs, Thomas Lengauer (Editor), 2001, John Wiley & Sons
• Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health), Warren Ewens, Gregory Grant, 2001, Springer Verlag
• Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, Second Edition, Andreas D. Baxevanis, B. F. Francis Ouellette, 2001, Wiley-Interscience
• Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning), Pierre Baldi, Soren Brunak, Sren Brunak, 2001, MIT Press
• Introduction to Bioinformatics, T eresa Attwood, David Parry-Smith, 2001, Prentice Hall
• Bioinformatics: A Primer, Charles Staben, 2001, Jones & Bartlett Pub
• Data Analysis and Classification for Bioinformatics, Arun Jagota, 2000, AKJ Academics
• Bioinformatics: Sequence and Genome Analysis, David W. Mount, 2001, Cold Spring Harbor Laboratory Press
• Bioinformatics: A Biologist's Guide to Biocomputing and the Internet, Stuart M. Brown, 2000, Eaton Pub Co
• Bioinformatics: Sequence, Structure and Databanks: A Practical Approach (The Practical Approach Series, 236), Des Higgins (Editor), Willie Taylor (Editor), 2000, Oxford Univ Press
• Neural Networks and Genome Informatics, Cathy H. Wu, Jerry W. McLarty, 2000, Elsevier Science
• Computational Molecular Biology: An Introduction (Wiley Series in Mathematical and Computational Biology), Peter Clote and Rolf Backofen, 2000, John Wiley & Sons
• Computational Molecular Biology: An Algorithmic Approach, Pavel A. Pevzner, 2000, MIT Press
• Post-Genome Informatics, Minoru Kanehisa, 2000, Oxford Univ Press
• Mathematical and Computational Biology: Computational Morphogenesis, Hierarchical Complexity, and Digital Evolution, Chrystopher L. Nehaniv, 1999, American Mathematical Society
• Pattern Discovery in Biomolecular Data: Tools, Techniques, and Applications, Jason T. L. Wang, Bruce A. Shapiro, Dennis Elliott Shasha (Editors), 1999, Oxford Univ Press
• Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison, David Sankoff and Joseph Kruskal (Editors), 1999, Cambridge University Press
• Bioinformatics Basics: Applications in Biological Science and Medicine, Hooman Rashidi, 1999, CRC Press
• Bioinformatics: Methods and Protocols (Methods in Molecular Biology, Vol 132), Stephen Misener and Stephen A. Krawetz (Editors),1999, Humana Press
• Bioinformatics: Databases and Systems, Stanley Letovsky (Editor),1999, Kluwer Academic Publishers
• Computational Molecular Biology, P. Green, 1998, Blackwell Science Inc.
• Computational Methods in Molecular Biology (New Comprehensive Biochemistry, V. 32), Steven L. Salzberg, David B. Searls, Simon Kasif (Editors), 1998, Elsevier Science Ltd.
• Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, Richard Durbin, S. Eddy, A. Krogh, G. Mitchison, 1998, Cambridge University Press
• Guide to Human Genome Computing, M. J. Bishop (Editor), 1998, Academic Press
• Introduction to Computational Molecular Biology, Joao Meidanis, Joao C. Setabal, 1997, PWS Pub. Co.
• Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology, Dan Gusfield, 1997, Cambridge University Press
• Sequence Data Analysis Guidebook, Simon R. Swindell (Editor), 1997, Humana Press
• High Performance Computational Methods for Biological Sequence Analysis, Tieng K. Yap, Ophir Frieder, Robert L. Martino, 1996, Kluwer Academic Pub.
• Computer Methods for Macromolecular Sequence Analysis, Methods in Enzymology, volume 266, Russell F. Doolittle (Editor), 1996, Academic Press
• DNA and Protein Sequence Analysis: A Practical Approach (Practical Approach Series , No 171), 1996, M. J. Bishop and C. J. Rawlings (Editors), 1996, IRL Press
• Molecular Bioinformatics: Algorithms and Applications, Steffen Schulze-Kremer, 1995, Walter De Gruyter
• Introduction to Computational Biology - Maps, sequences and genomes, Michael S. Waterman, 1995, Chapman & Hall
• Computer Analysis of Sequence Data, Annette M. Griffin and Hugh G. Griffin (Editors), 1994, Humana Press
• Artificial Intelligence and Molecular Biology, Lawrence Hunter (Editor), 1993, AAAI Press
• Sequence Analysis Primer, Michael Gribskov and John Devereux (Editors), 1992, Oxford University Press
• Mathematical Methods of Analysis of Biopolymer Sequences (Dimacs Series in Discrete Mathematics and Theoretical Computer Science ; Volume 8), S. G. Gindikin, 1992, American Mathematical Society
• Mathematical Methods for DNA Sequences, Michael S. Waterman (Editor), 1989, CRC Press

Programming Books for Bioinformatics

• Mastering Perl for Bioinformatics, James D. Tisdall, 2003, O'Reilly
• Genomic Perl: From Bioinformatics Basics to Working Code, Rex A. Dwyer, 2002, Cambridge University Press
• Beginning Perl for Bioinformatics, James Tisdall, 2001, O'Reilly
• Developing Bioinformatics Computer Skills, Cynthia Gibas, Per Jambeck, 2001, O'Reilly

General Genomics

• Functional Microbial Genomics (Volume 33), Brendan Wren, Nick Dorrell, 2003, Academic Press
• Discovering Genomics, Proteomics, and Bioinformatics, A. Malcolm Campbell, Laurie J. Heyer, 2002, Benjamin/Cummings
• Genomes, Terence A. Brown, 2002, John Wiley & Sons
• Essentials of Medical Genomics, Stuart M. Brown , 2002, John Wiley & Sons
• A Primer of Genome Science, Greg Gibson, Spencer V. Muse, 2002, Sinauer Associates
• Pathogen Genomics: Impact on Human Health, Karen Joy, Phd Shaw (Editors), 2002, Humana Press
• Genomics, John E. Antonopoulos, 2000, Xlibris Corporation
• Genomics and Proteomics: Functional and Computational Aspects, Sandor Suhai (Editor), 2000, Plenum Pub Corp
• Functional Genomics: A Practical Approach (The Practical Approach Series, 235), S. Hunt and F. Livesey (Editors), 2000, Oxford Univ Press
• Human Molecular Genetics, Andrew P. Read, Tom Strachan 1999, BIOS Scientific Publishers Ltd.
• Genomics: The Science and Technology Behind the Human Genome Project, Charles R. Cantor and Cassandra L. Smith, 1999, John Wiley & Sons
• Cells: A Laboratory Manual, 3 volumes, David L. Spector, Robert D. Goldman, Leslie A. Leinwand, 1998, Cold Spring Harbor Laboratory Press
• Genome Analysis: A Laboratory Manual, 4 volumes, Bruce Birren, et al. (Editors), 1997, Cold Spring Harbor Laboratory Press
• The Human Genome Project, N. G. Cooper (Editor), 1994, University Science Books

Comparative Genomics

• Handbook of Comparative Genomics: Principles and Methodology, Cecilia Saccone, Graziano Pesole, 2003, Wiley-Liss
• Sequence - Evolution - Function: Computational Approaches in Comparative Genomics, Eugene V. Koonin, Michael Y. Galperin, 2002, Kluwer Academic Publishers
• Comparative Genomics - Empirical and Analytical Approaches to Gene Order Dynamics, Map Alignment and the Evolution of Gene Families, David Sankoff and Joseph H. Nadeau, 2000, Kluwer Academic Pub
• Comparative Genomics, Melody Clark (Editor), 2000, Kluwer Academic Pub

Proteomics

• Proteins and Proteomics: A Laboratory Manual, Richard J. Simpson (Editor), Cold Spring Harbor Laboratory
• Proteomics in Practice: A Laboratory Manual of Proteome Analysis , Reiner Westermeier, Tom Naven, 2002, John Wiley & Sons
• Posttranslational Modifications of Proteins: Tools for Functional Proteomics (Methods in Molecular Biology, Vol 194) , Christoph Kannicht (Editor), 2002, Humana Press
• Peptide Arrays on Membrane Supports: Synthesis and Applications (Springer Lab Manual), Joachim Koch, Michael Mahler (Editors), 2002, Springer Verlag
• Proteomics , Timothy Palzkill, 2002, Kluwer Academic Publishers
• Introduction to Proteomics: Tools for the New Biology , Daniel C. Liebler (Editor), 2001, Humana Press
• Proteome Research: Mass Spectrometry (Principles and Practice) , P. James (Editor), 2001, Springer Verlag
• Interpreting Protein Mass Spectra: A Comprehensive Resource , A. Peter Snyder, 2000, American Chemical Society
• Protein Sequencing and Identification Using Tandem Mass Spectrometry , Michael Kinter, Nicholas E. Sherman, 2000, Wiley-Interscience
• From Genome to Proteome: Advances in the Practice and Application of Proteomics, Michael J. Dunn (Editor), 2000, Vch Verlagsgesellschaft Mbh
• Proteomics: From Protein Sequence to Function, S. Pennington (Editor), M. Dunn (Editor), 2000, Springer Verlag
• Proteome Research: Two-Dimensional Gel Electrophoresis and Detection Methods (Principles and Practice), T. Rabilloud (Editor), 2000, Springer Verlag
• Proteome and Protein Analysis, R. M. Kamp, D. Kyriakidis, th Choli-Papadopoulou (Editor), 1999, Springer Verlag
• Proteome Research: New Frontiers in Functional Genomics, M. R. Wilkins, et al. (Editors), 1997, Springer Verlag

Protein Structure

• Structural Bioinformatics, Philip E. Bourne, Helge Weissig (Editors), 2003, John Wiley & Sons
• Protein Structure Prediction: Bioinfomatic Approach, I.F. Tsigelny, 2002, International University Line
• Introduction to Protein Architecture: The Structural Biology of Proteins, Arthur M. Lesk, 2001, Oxford University Press
• Protein Structure Prediction: Methods and Protocols, David M. Webster (Editor), 2000, Humana Press
• Introduction to Protein Structure, Carl-Ivar Branden, John Tooze, 1999, Garland Publishing
• Structure and Mechanism in Protein Science: A Guide to Enzyme Catalysis and Protein Folding, Alan Fersht, 1999, Freeman

Pharmacogenomics

• Pharmacogenomics: Social, Ethical, and Clinical Dimensions, Mark A. Rothstein (Editor), 2003, Wiley-Liss
• Pharmacogenomics: The Search for Individualized Therapies, Julio Licinio, Ma-Li Wong (Editors), 2002, John Wiley & Sons
• Pharmacogenomics, Werner Kalow, Urs A. Meyer, Rachel Tyndale (Editors), 2001, Marcel Dekker
• Pharmacogenetics and Pharmcogenomics: Recent Conceptual and Technical Advances (Pharmacology, Volume 61, Number 3, 2000), Elliot S. Vesell (Editor), 2000, S. Karger Publishing
• Pharmacogenetics, Wendell Weber, 1997, Oxford University Press

DNA Microarrays

• Statistical Analysis of Gene Expression Microarray Data, T. P. Speed (Editor), 2003, CRC Press
• Microarray Gene Expression Data Analysis: A Beginner's Guide, Helen C. Causton, John Quackenbush, Alvis Brazma, 2003, Blackwell Publishers
• The Analysis of Gene Expression Data (Statistics for Biology and Health), G. Parmigiani, E. S. Garrett, R. A. Irizarry, S. Zeger , Graeme Clark (Editors), 2003, Springer Verlag
• A Practical Approach to Microarray Data Analysis, Daniel P. Berrar, Werner Dubitzky, Martin Granzow (Editors), 2002, Kluwer Academic Publishers
• DNA Microarrays and Gene Expression: From Experiments to Data Analysis and Modeling, Pierre Baldi, G. Wesley Hatfield, 2002, Cambridge University Press
• DNA Microarrays: A Molecular Cloning Manual, David Bowtell, Joseph Sambrook (Editors), 2002, Cold Spring Harbor Laboratory
• DNA Array Image Analysis: Nuts & Bolts, Gerda Kamberova, Shishir Shah, 2002, DNA Press
• Microarray Analysis, Mark Schena, 2002, John Wiley & Sons
• A Biologist's Guide to Analysis of DNA Microarray Data, Steen Knudsen, 2002, John Wiley & Sons
• Microarrays for an Integrative Genomics (Computational Molecular Biology), Isaac S. Kohane, Alvin Kho, Atul J. Butte, 2002, MIT Press
• Microarrays for the Neurosciences: An Essential Guide (Cellular and Molecular Neuroscience), Daniel H. Geschwind, Jeffrey P. Gregg (Editors), 2002, MIT Press
• DNA Microarrays: Gene Expression Applications, Bertrand Jordan (Editor), 2001, Springer Verlag
• DNA Arrays: Methods and Protocols (Methods in Molecular Biology, Volume 170), Jang B. Rampal (Editor), 2001, Humana Press
• DNA Arrays: Technologies and Experimental Strategies, Elena V. Grigorenko (Editor), 2001, CRC Press
• Microarray Biochip Technology, Mark Schena (Editor), 2000, Eaton Pub
• Expression Genetics: Accelerated and High-Throughput Methods (Biotechniques Update Series), Michael McClelland (Editor), Arthur B. Pardee (Editor), 1999, Eaton Pub
• DNA Microarrays: A Practical Approach (Practical Approach Series 205), Mark Schena (Editor), 1999, Oxford Univ Press
• cDNA Preparation and Characterization (Methods in Enzymology Volume 303), S.M. Weissman (Editor), 1999, Academic Press

Systems Biology, Genetic and Biochemical Network

• Handbook of Graphs and Networks : From the Genome to the Internet, Stefan Bornholdt, Heinz Georg Schuster (Editors), 2003, Vch Verlagsgesellschaft Mbh
• Computational Cell Biology, Christopher Fall, Eric Marland, John Wagner, John Tyson (Editors), 2002, Springer Verlag
• Gene Regulation and Metabolism: Post-Genomic Computational Approaches (Computational Molecular Biology), Julio Collado-Vides, Ralf Hofestadt (Editors), 2002, MIT Press
• Foundations of Systems Biology, Hiroaki Kitano (Editor), 2001, MIT Press
• Genomic Regulatory Systems: Development and Evolution, Eric H. Davidson , 2001, Academic Press
• Genes & Signals, Mark Ptashne, Alexander Gann, 2001, Cold Spring Harbor Laboratory
• Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology), James M. Bower and Hamid Bolouri (Editors), 2001, MIT Press
• Protein-Protein Interactions: A Molecular Cloning Manual, Erica Golemis (Editor), 2001, Cold Spring Harbor Laboratory
• Computational Analysis of Biochemical Systems: A Practical Guide for Biochemists and Molecular Biologists, Eberhard O. Voit, 2000, Cambridge University Press
• Mathematical Physiology, James P. Keener, James Sneyd, 1998, Springer Verlag

DNA Sequencing

• DNA Sequencing: From Experimental Methods to Bioinformatics (Introduction to Biotechniques Series), Luke Alphey, 1997, Springer Verlag
• Automated DNA sequencing and analysis, Adams M.D., Fields C., Venter J.C. (Editors), 1994, Academic Press

Apart from above mentioned books, you can also find some useful books links at following mentioned URLs:

http://www.amazon.com/Biological-Sequence-Analysis-Probabilistic-Proteins/dp/0521629713

http://www.amazon.com/Bioinformatics-Genes-Proteins-Computers-Advanced/dp/1859960545

http://www.amazon.com/Introduction-Bioinformatics-Algorithms-Computational-Molecular/dp/0262101068

http://books.google.no/books?id=pxSM7R1sdeQC&dq=Pierre+baldi+%2B+bioinformatics&printsec=frontcover&source=bn&hl=en&ei=IoGRS6uCIJT-NYLA8Z0N&sa=X&oi=book_result&ct=result&redir_esc=y#v=onepage&q&f=false

http://www.amazon.com/Statistical-Methods-Bioinformatics-Introduction-Statistics/dp/0387400826

If you think your favourite books are not listed then please write it down in comment section for the benefits of other users. Feel free to add many more books in comment section. 

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/23/14/1713.full

Read more: https://edu.t-bio.info/amity-university-summer-bioinformatics-program-registrations-are-open/

Address of the bookmark: https://bioinformatik.de/en/bioinformatics-in-germany/research/research-groups.html