BOL: Related items

Tetra-Nucleotide Analysis

Jit — Thu, 04 May 2017 05:07:41 -0500

A tetra-nucleotide is a fragment of DNA sequence with 4 bases (e.g. AGTC or TTGG). Pride et al. (2003) showed that the frequency of tetra-nucleotides in bacterial genomes contain useful, albeit weak, phylogenetic signals. Even though tetra-nucleotide analysis (TNA) utilizes the information of whole genome, it is evident that it cannot replace other alignment-based phylogenetic methods such as OrthoANI or 16S rRNA phylogeny. However, TNA can be useful for phylogenetic characterization when whole genome or 16S rRNA gene information is not available. For example, a partial genomic fragment obtained from a metagenome can be identified by TNA (Teeling et al., 2004). TNA is also fast enough that it can be used as a search engine against a large genome database.

Address of the bookmark: https://chunlab.wordpress.com/tetra-nucleotide-analysis/

Bioinformatics Scientist, Production Bioinformatics @ South San Francisco, CA

Thu, 19 Aug 2021 08:45:24 -0500

wist is looking for a Bioinformatics Scientist to join our Production Bioinformatics Team. You will work alongside research scientists, software engineers and data scientists to further deliver on our mission to expand access to best-in-class synthetic biology and next-generation sequencing applications. You will be developing and engineering tools to better evaluate and build hardened, production quality pipelines, optimize data quality, and automate lab and bioinformatics processes. Our ideal candidate is an organized problem solver with a background in developing and building novel production-quality bioinformatics tools and packages. Equally excellent communication skills and a proven ability to work independently are required.

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

A Beginner's Guide to Using Kraken for Taxonomic Classification

Neel — Fri, 13 Dec 2024 11:29:03 -0600

Kraken is a popular bioinformatics tool designed for fast and accurate taxonomic classification of metagenomic sequences. Its efficiency and precision make it a go-to resource for analyzing microbial communities, including bacteria, viruses, archaea, and fungi. Whether you're new to bioinformatics or experienced in the field, Kraken is an indispensable tool for taxonomic analysis.

In this blog, we’ll walk through the basics of Kraken, from installation to running an analysis, and highlight its key features and applications.

What is Kraken?

Kraken is a sequence classification tool that assigns taxonomic labels to DNA sequences using exact k-mer matching. It uses a reference database of genomes, dividing sequences into k-mers and identifying matches in a computationally efficient way.

Key Features of Kraken

Speed: Kraken processes data much faster than alignment-based methods.
Accuracy: It uses a precise k-mer matching algorithm for high-resolution taxonomic assignments.
Scalability: It can handle large metagenomic datasets.
Custom Databases: You can build and use custom databases tailored to your research needs.

Installing Kraken

System Requirements
- A Unix-based operating system (Linux/macOS).
- Sufficient computational resources for database building (RAM and disk space).
Installation Steps
- Clone the Kraken repository from GitHub:
  
  git clone https://github.com/DerrickWood/kraken.git cd kraken
- Compile the Kraken binaries:
  
  make
- Add Kraken to your PATH for easy access:
  
  export PATH=$PATH:/path/to/kraken

Preparing a Database

Kraken requires a database of reference genomes. You can use a pre-built database or create a custom one.

Downloading a Pre-built Database
Kraken offers pre-built databases, such as the MiniKraken database, which is lightweight and suitable for smaller datasets. Download it using:

kraken-build --download-library minikraken
Building a Custom Database
To include specific genomes, download FASTA files and build the database:

kraken-build --download-library bacteria --threads 4 --db my_database kraken-build --build --db my_database

This process may take considerable time and resources, depending on the size of the database.

Running Kraken

Once the database is ready, you can classify sequences.

Basic Usage
Use the following command to classify sequences:

kraken --db my_database --threads 4 --fastq-input input_sequences.fastq --output kraken_output.txt

Key options:
- --db: Specifies the database.
- --threads: Number of threads for parallel processing.
- --fastq-input: Indicates input file format (FASTQ/FASTA).
Interpreting Results
Kraken generates an output file with columns for sequence IDs, taxonomic classifications, and the confidence score.

Visualizing Kraken Results

Kraken results can be visualized using tools like Krona or converted to human-readable reports using kraken-report.

Generate a Report

kraken-report --db my_database kraken_output.txt > kraken_report.txt
Krona Visualization
Install Krona and convert Kraken output for visualization:

cut -f2,3 kraken_output.txt | ktImportTaxonomy -o krona_output.html

Open the HTML file in your browser to interactively explore the taxonomic classifications.

Advanced Usage

Confidence Thresholds
Adjust the confidence threshold for classification using the --confidence option. Higher values reduce false positives but may miss some true positives:

kraken --db my_database --confidence 0.1 --fastq-input input.fastq
Paired-End Reads
For paired-end sequencing data, use:

kraken --db my_database --paired reads_1.fastq reads_2.fastq
Customizing K-mers
Kraken allows you to set custom k-mer lengths during database building for specific applications.

Applications of Kraken

Microbial Ecology: Characterizing microbial communities in soil, water, and the human microbiome.
Pathogen Detection: Identifying pathogens in clinical samples.
Fungal Research: Analyzing fungal diversity in metagenomic datasets.
Environmental Monitoring: Tracking microbial populations in diverse habitats.

Conclusion

Kraken is a versatile and efficient tool for taxonomic classification in metagenomics. Its speed, accuracy, and flexibility make it a favorite among bioinformaticians. By following this guide, you can set up and use Kraken to unlock insights into microbial and fungal communities, paving the way for discoveries in ecology, medicine, and biotechnology.

BioCircos.js is an open source interactive Javascript library to interactive display biological data on the web

Jit — Fri, 19 Jan 2018 15:03:51 -0600

BioCircos.js is an open source interactive Javascript library which provides an easy way to interactive display biological data on the web. It implements a raster-based SVG visualization using the open source Javascript framework jquery.js. BioCircos.js is multiplatform and works in all major internet browsers (Internet Explorer, Mozilla Firefox, Google Chrome, Safari, Opera). Its speed is determined by the client’s hardware and internet browser. For smoothest user experience, we recommend Google Chrome.

BioCircos.js provides SNP, CNV, HEATMAP, LINK, LINE, SCATTER, ARC, TEXT, and HISTGRAMmodules to display genome-wide genetic variations (SNPs, CNVs and chromosome rearrangement), gene expression and biomolecule interactions. BioCircos.js also provides BACKGROUND module to display background and axis circles. Tooltips showing detailed information of SVG elements are also provided.

Demo

Address of the bookmark: http://bioinfo.ibp.ac.cn/biocircos/document/index.html

k-mers tutorial - classification and taxonomy

Neel — Thu, 26 Aug 2021 10:28:43 -0500

DNA k-mers underlie much of our assembly work, and we (along with many others!) have spent a lot of time thinking about how to store k-mer graphs efficiently, discard redundant data, and count them efficiently.

More recently, we've been enthused about using k-mer based similarity measures and computing and searching k-mer-based sketch search databases for all the things.

But I haven't spent too much talking about using k-mers for taxonomy, although that has become an ahem area of interest recently, if you read into our papers a bit.

In this blog post I'm going to fix this by doing a little bit of a literature review and waxing enthusiastic about other people's work. Then in a future blog post I'll talk about how we're building off of this work in fun! and interesting? ways!

Address of the bookmark: http://ivory.idyll.org/blog/2017-something-about-kmers.html

Interactive Market Intelligence

Pranjali Yadav — Mon, 19 Jan 2015 08:20:38 -0600

BioInformatics LLC, a premier research and advisory firm serving the life science industry, has launched groundbreaking, dynamic-data presentation platform, Interactive Market Intelligence— the only cloud-based market research analytics tool for the life science tools industry.

Superior to traditional PDF and PowerPoint reports, Interactive Market Intelligence allows end-users to filter, create and export literally thousands of views of data — all easily obtainable from a set of core metrics that include market, brand, customer and workflow analytics in well-defined segments of the life science market.

The Market for Real-Time PCR is the first in a series of topics to be explored using the Interactive Market Intelligence platform. The primary research analysis is based on a survey of 900+ international scientists performing qPCR in their laboratories.

Key data findings from "The Market for Real-Time PCR": Global market for qPCR in 2015 is estimated to be $3.6B; The average growth in qPCR throughput is expected to be at 9.8% in 2015; 22% of respondents are highly likely to switch primary suppliers of qPCR products; 50% of respondents use pre-designed primer/probe sets.

Post-doc position at LABGeM - Evry, France

Fri, 11 Dec 2015 06:24:00 -0600

The LABGeM team (CEA/Genoscope, CNRS UMR 8030, France, Dir. Claudine Médigue) is developing integrated approaches which combines bioinformatics methods based (i) on genomic and metabolic contexts, (ii) on an orignal metabolic network representation and (iii) on a structural classification of active sites for the discovery of new metabolic enzymatic activities.

We are hiring a post-doctoral fellow for the development of innovative bioinformatics methods to explore metabolic networks and enzyme families. These methods will be based on protein family analysis and graph approaches combining genomic and metabolic contexts.

For more details, please see this link : http://goo.gl/tHQOqk

Qualifications:
PhD degree in bioinformatics or computational biology
- Previous experience in network or protein family analysis
- Programming skills (C/C++, Python, Java) and in common biostatistical analyses
- Team player, innovative and creative thinking, good oral and written communication skills

24 months, Post Doctoral position
Start: from March 2016
Place: CEA, Genoscope UMR8030, LABGeM (Laboratory of Bioinformatics Analyses for Genomics and Metabolism), Evry, France
Contact: David Vallenet, vallenet@genoscope.cns.fr
Publications: https://scholar.google.com/citations?user=rJNPLSAAAAAJ
Remuneration per month: from 2,850 €

Interested candidates should send their CV, statement of research interests, and contact information of at least 2 references to David Vallenet (vallenet@genoscope.cns.fr).

MEGAN6

Neel — Mon, 25 Jul 2016 05:45:22 -0500

Microbiome analysis using a single application

MEGAN6 is a comprehensive toolbox for interactively analyzing microbiome data. All the interactive tools you need in one application.

Taxonomic analysis using the NCBI taxonomy or a customized taxonomy such as SILVA
Functional analysis using InterPro2GO, SEED, eggNOG or KEGG
Bar charts, word clouds, Voronoi tree maps and many other charts
PCoA, clustering and networks
Supports metadata
MEGAN parses many different types of input

Why use MEGAN6?

The software is:

Easy to use. MEGAN6 is a single application and all features are available through menus, toolbars and graphics. No scripting skills required.
Powerful. MEGAN6 allows you to work with hundreds of samples containing hundreds of millions of sequencing reads. Blast-like analysis can be performed using DIAMOND.
Comprehensive. MEGAN6 offers a large range of analysis tools, and is under active development.

Address of the bookmark: https://ab.inf.uni-tuebingen.de/software/megan6

ABACAS

Surabhi Chaudhary — Thu, 16 Feb 2017 12:15:55 -0600

ABACAS is intended to rapidly contiguate (align, order, orientate) , visualize and design primers to close gaps on shotgun assembled contigs based on a reference sequence. It uses MUMmer to find alignment positions and identify syntenies of assembly contigs against the reference. The output is then processed to generate a pseudomolecule taking overlaping contigs and gaps in to account. MUMmer's alignment generating programs, Nucmer and Promer are used followed by the 'delta-filter' utility function. Users could also run tblastx on contigs that are not used to generate the pseudomolecule.

Address of the bookmark: http://abacas.sourceforge.net/Manual.html#9._Colour_code

Best book Titles for Learning Bionformatics

Rahul Agarwal — Tue, 13 Aug 2013 17:31:51 -0500

Nothing can add to our intellect more than reading a book. In books, we can experience new things that we would not normally be able to experience. It is proved that books can change our lives and other people’s lives. Reading can make us more intelligent, updated, imaginative. Without reading we wouldn’t know anything that we know today. There are several book, online and offile to read and I can't mentioned all of them here in the list. Therefore, I mentioned some bioinformatics and its related books in subgroups. Hope you will like the list.

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.