A Practical Approach to Microarray Data Analysis

A Practical Approach to Microarray Data Analysis is for all life scientists, statisticians, computer experts, technology developers, managers, and other professionals tasked with developing, deploying, and using microarray technology including the necessary computational infrastructure and analytical tools. The book addresses the requirement of scientists and researchers to gain a basic understanding of microarray analysis methodologies and tools. It is intended for students, teachers, researchers, and research managers who want to understand the state of the art and of the presented methodologies and the areas in which gaps in our knowledge demand further research and development. The book is designed to be used by the practicing professional tasked with the design and analysis of microarray experiments or as a text for a senior undergraduate- or graduate level course in analytical genetics, biology, bioinformatics, computational biology, statistics and data mining, or applied computer science.
Key topics covered include:
-Format of result from data analysis, analytical modeling/experimentation;
-Validation of analytical results;
-Data analysis/Modeling task;
-Analysis/modeling tools;
-Scientific questions, goals, and tasks;
-Application;
-Data analysis methods;
-Criteria for assessing analysis methodologies, models, and tools

Download

Structure and Interpretation of Computer Programs (SICP)

Structure and Interpretation of Computer Programs (SICP) is a textbook published in 1984 about general computer programming concepts from MIT Press written by Massachusetts Institute of Technology (MIT) professors Harold Abelson and Gerald Jay Sussman, with Julie Sussman. It was formerly used as the textbook of MIT introductory programming class and at other schools.

Using a dialect of the Lisp programming language known as Scheme, the book explains core computer science concepts, including abstraction, recursion, interpreters and metalinguistic abstraction, and teaches modular programming.
The program also introduces a practical implementation of the register machine concept, defining and developing an assembler for such a construct, which is used as a virtual machine for the implementation of interpreters and compilers in the book, and as a testbed for illustrating the implementation and effect of modifications to the evaluation mechanism. Working Scheme systems based on the design described in this book are quite common student projects.

Download 

Computational Biology: Genomes, Networks, Evolution

Lecture Slides

Lecture 1
Course Overview and Outline - Intro to Biology - Why Computational Biology - Regulatory Motif discovery

Lecture 2 - Sequence Alignment + Dynamic Programming
Fibonacci - Paths & Alignments - Bounded DP - Linear Space Alignment

Lecture 3 - Sequence Alignment II
Globa/Local/Semi-global alignment + Affine gaps + Alignment statistics

Lecture 4 - Exact string matching
Semi-numerical methods, prelude to hashing

Lecture 5 - Hashing + Blast
Database search - Hashing - Blast - Extensions - Combs - Suffix Trees

Lecture 6 - Modeling Biological Sequences with HMMs
Dishonest Casino, CpG islands, Markov Chains, HMMs, Viterbi

Lecture 7 - HMM decoding evaluation training
Viterbi+Decoding, Forward+Evaluation, Backward+Posterior Decoding, BaumWelch+Training

Lecture 8 - Clustering gene expression data 

Lecture 9 - Clustering and Dimensionality Reduction
Running time analysis, feature selection, SVD, PCA

Lecture 10 - Regulatory Motif Discovery
Combinatorial/probabilistic formulation, weight matrices, gibbs sampling, EM

Lecture 11 - Graph algorithms
Connected components, spectral partitioning

Lecture 12 - Evolutionary trees 

Evolution, trees, distance-based methods, parsimony 

Lecture 13 - Phylogenetics
Jukes-Cantor, Kimura, ultrametric, additive, UPGMA, Neighbor-Joining, Dynamic programming parsimony

Lecture 15 - RNA folding
RNA folding - Nussinov's algorithm - Zucker's algorithm - context-free grammars - parsing

Lecture 16 - Stochastic Context-Free Grammars
CYK algorithm - Inside/Outside - HMM similarity - Posterior decoding

Lecture 17 - Genome Rearrangements
Evolution by rearrangements - Sorting by reversals - greedy algorithms - approximation algorithms - breakpoint graphs

Lecture 18 - Genome Duplication
Orthologs - Paralogs - Phylogenetic Tree Reconciliation - Genome Duplication - Duplicate gene divergence - Accelerated Evolution

Lecture 19: Genome assembly
Sequencing, assembly, whole genome shotgun, hierarchical approach

Lecture 22 - Biological Networks
Guest lecture by Laszlo Barabasi - Scale-free networks - Network growth - Robustness - Modularity - Hierarchical - Flux

Lecture 23 - Advanced Multiple Alignment and Assembly
Traditional assembly - String-graph assembly - Global and glocal alignment - Alignmnet with polymorphism

Lecture 24 - Whole-Genome Analysis
HMMs for Gene Finding - Classification based gene finding - Human Motif Finding - MicroRNA regulation

Recitation Notes

Recitation 1 - Running Times, Molecular Biology and Probability

Recitation 2 - Python and Dynamic Programming and Alignments 

Recitation 3 - Randomization, Modulus, Hashing, Random Projections, BLAST, Suffix Trees 

Recitation 4 - Hidden Markov Models 

Recitation 6 - Motif Finding Using EM and Gibbs Sampling

Recitation 7 - UPGMA, Neighbor Joining, Parsimony 

Recitation 8 - RNA Folding, Context Free Grammars and Related Algorithms

Recitation 9 - Sequencing by Hybridization 

Problem Sets

Problem Set 1     

Problem Set 2     

Problem Set 3    

Problem Set 4    

Problem Set 5    

Listen about Bioinformatics....

One More is here

An Introduction to Genetic Algorithms- Melanie Mitchell

Science arises from the very human desire to understand and control the world. Over the course of history, we humans have gradually built up a grand edifice of knowledge that enables us to predict, to varying extents, the weather, the motions of the planets, solar and lunar eclipses, the courses of diseases, the rise and fall of economic growth, the stages of language development in children, and a vast panorama of other natural, social, and cultural phenomena. More recently we have even come to understand some fundamental limits to our abilities to predict. Over the eons we have developed increasingly complex means to control many aspects of our lives and our interactions with nature, and we have learned, often the hard way, the extent to which other aspects are uncontrollable.

The advent of electronic computers has arguably been the most revolutionary development in the history of science and technology. This ongoing revolution is profoundly increasing our ability to predict and control nature in ways that were barely conceived of even half a century ago. For many, the crowning achievements of this revolution will be the creation—in the form of computer programs—of new species of intelligent beings, and even of new forms of life.

The goals of creating artificial intelligence and artificial life can be traced back to the very beginnings of the computer age. The earliest computer scientists—Alan Turing, John von Neumann, Norbert Wiener, and others—were motivated in large part by visions of imbuing computer programs with intelligence, with the life−like ability to self−replicate, and with the adaptive capability to learn and to control their environments. These early pioneers of computer science were as much interested in biology and psychology as in electronics, and they looked to natural systems as guiding metaphors for how to achieve their visions. It  should be no surprise, then, that from the earliest days computers were applied not only to calculating missile trajectories and deciphering military codes but also to modeling the brain, mimicking human learning, and simulating biological evolution. These biologically motivated computing activities have waxed and waned over the years, but since the early 1980s they have all undergone a resurgence in the computation research community. The first has grown into the field of neural networks, the second into machine learning, and the third into what is now called "evolutionary computation," of which genetic algorithms are the most prominent example

Read

DNA Molecular Structure and Dynamics

Author: I.C. Baianu, editor with several contributors

Description

A concise overview with color image galleries of important DNA molecular dynamics applications to computing and quantum computations of DNA structure and dynamics.

Includes several image galleries with instrumentation, techniques and contributed brilliant images. 113-page textbook PDF of 24 Mb, May 25th, 2009.

     Read

The Forbidden Combinations of Amino acids & Genetic Codes (codons)

The Forbidden Combinations of Amino acids & Genetic Codes (codons)



The proteogenic amino acids tryptophan, cysteine, and methionine have only a single codon for each in the table of universal genetic code. The relative frequency of each of these codons is 1.5625%. Strikingly, the relative distribution of these amino acids in enzymes is also invariably less than 3.0% irrespective of the class and  type of the reaction catalyzed.  The amino acids other than tryptophan, cysteine and methionine show variable distributions.  One would also find that the following genetic code combinations are  very rare  in nature. There are some hypothetical, predicted, or cloned sequences and proteins in the databases like NCBI. But, none of them are natural.The list of forbidden genetic code combinations:

1.  TGGTGTATG   corresponding to the amino acid combination WCM
2.  TGGATGTGT   corresponding to the amino acid combination WMC
3.  TGTATGTGG   corresponding to the amino acid combination CMW
4.  TGTTGGATG   corresponding to the amino acid combination CWM
5.  ATGTGTTGG  corresponding to the amino acid combination MCW
6.  ATGTGGTGT  corresponding to the amino acid combination MCW

Based on these observations, I conclude that nature does not allow all the genetic code combinations to occur with equal probability. If the combinations occur equally likely, then one should observe these combinations with the same relative frequency as those of other code combinations. Why nature forbids such combinations is yet to be answered. Is it biophysically restricted or is it a genetic restriction? These are unanswered questions. 
One could also make proteins, if possible, with these restricted combinations (either by site directed
mutagenesis or by solid state synthesis) and study their biophysical properties. The above observation is purely based on the data available from the NCBI and RCSB. 

To verify this claim:
1. Run blastp at http://blast.ncbi.nlm.nih.gov/Blast.cgi   for  wcmwmccmwcwmmcwmwc and check the output, check for the proteins, find whether they are hypothetical or biochemically characterized.
2. Run blastn at http://blast.ncbi.nlm.nih.gov/Blast.cgi   for  TGGTGTATGAAAAAAAAAAA, 
TGGATGTGTAAAAAAAAAAA, TGTATGTGGAAAAAAAAAAA, TGTTGGATGAAAAAAAAAAA,
ATGTGTTGGAAAAAAAAAAA, ATGTGGTGTAAAAAAAAAAA, and check each output. One would find similar sequences only, no exact match (except some clones).


Sivashanmugam. P., Lecturer, Biophysical Chemistry, 
Department of Bioinformatics, Jamal Mohamed College, Tiruchirappalli – 620020 – India
e-mail: soundaryanayaki@aol.com

RNA Processing

• 

RNA functions broadly as informational molecule, genome, enzyme and machinery for RNA processing. While these functions reflect ancient activities, they also remain vital components of contemporary biochemical pathways. In eukaryotic cells RNA processing impacts the biogenesis of RNA molecules of essentially every shape and function. The collection of articles in this volume describes the current state of understanding of the broad array of RNA processing events in animal and plant cells, key unanswered questions, and cutting edge approaches available to address these questions. Some questions discussed in this volume include, how viruses subvert the RNA processing machinery of the host cell, how the coordination of co-transcriptional RNA processing is regulated at the level of chromatin, the status of RNA processing in plant organelles, and how micro RNA machinery is biosynthesized and regulated.

Download for Free

Protein Engineering

• 

A broad range of topics are covered by providing a solid foundation in protein engineering and supplies readers with knowledge essential to the design and production of proteins. This volume presents in-depth discussions of various methods for protein engineering featuring contributions from leading experts from different counties. A broad series of articles covering significant aspects of methods and applications in the design of novel proteins with different functions are presented. These include the use of non-natural amino acids, bioinformatics, molecular evolution, protein folding and structure-functional insight to develop useful proteins with enhanced properties.

Download For Free

Integrative Proteomics

• 

Proteomics was thought to be a natural extension after the field of genomics has deposited significant amount of data. However, simply taking a straight verbatim approach to catalog all proteins in all tissues of different organisms is not viable. Researchers may need to focus on the perspectives of proteomics that are essential to the functional outcome of the cells. In Integrative Proteomics, expert researchers contribute both historical perspectives, new developments in sample preparation, gel-based and non-gel-based protein separation and identification using mass spectrometry. Substantial chapters are describing studies of the sub-proteomes such as phosphoproteome or glycoproteomes which are directly related to functional outcomes of the cells. Structural proteomics related to pharmaceutics development is also a perspective of the essence. Bioinformatics tools that can mine proteomics data and lead to pathway analyses become an integral part of proteomics. Integrative proteomics covers both look-backs and look-outs of proteomics. It is an ideal reference for students, new researchers, and experienced scientists who want to get an overview or insights into new development of the proteomics field.

Download For Free

Molecular Interactions

• 

In a classical approach materials science is mainly dealing with interatomic interactions within molecules, without paying much interest on weak intermolecular interactions. However, the variety of structures actually is the result of weak ordering because of noncovalent interactions. Indeed, for self-assembly to be possible in soft materials, it is evident that forces between molecules must be much weaker than covalent bonds between the atoms of a molecule. The weak intermolecular interactions responsible for molecular ordering in soft materials include hydrogen bonds, coordination bonds in ligands and complexes, ionic and dipolar interactions, van der Waals forces, and hydrophobic interactions. Recent evolutions in nanosciences and nanotechnologies provide strong arguments to support the opportunity and importance of the topics approached in this book, the fundamental and applicative aspects related to molecular interactions being of large interest in both research and innovative environments. We expect this book to have a strong impact at various education and research training levels, for young and experienced researchers from both academia and industry.

Download For Free

Protein-Protein Interactions - Computational and Experimental Tools

 

Proteins are indispensable players in virtually all biological events. The functions of proteins are coordinated through intricate regulatory networks of transient protein-protein interactions (PPIs). To predict and/or study PPIs, a wide variety of techniques have been developed over the last several decades. Many in vitro and in vivo assays have been implemented to explore the mechanism of these ubiquitous interactions. However, despite significant advances in these experimental approaches, many limitations exist such as false-positives/false-negatives, difficulty in obtaining crystal structures of proteins, challenges in the detection of transient PPI, among others. To overcome these limitations, many computational approaches have been developed which are becoming increasingly widely used to facilitate the investigation of PPIs. This book has gathered an ensemble of experts in the field, in 22 chapters, which have been broadly categorized into Computational Approaches, Experimental Approaches, and Others.

Download For Free

Molecular Dynamics - Studies of Synthetic and Biological Macromolecules

Molecular Dynamics is a two-volume compendium of the ever-growing applications of molecular dynamics simulations to solve a wider range of scientific and engineering challenges. The contents illustrate the rapid progress on molecular dynamics simulations in many fields of science and technology, such as nanotechnology, energy research, and biology, due to the advances of new dynamics theories and the extraordinary power of today's computers. This second book begins with an introduction of molecular dynamics simulations to macromolecules and then illustrates the computer experiments using molecular dynamics simulations in the studies of synthetic and biological macromolecules, plasmas, and nanomachines. Coverage of this book includes: Complex formation and dynamics of polymers Dynamics of lipid bilayers, peptides, DNA, RNA, and proteins Complex liquids and plasmas Dynamics of molecules on surfaces Nanofluidics and nanomachines

Download For Free

Protein Structure

Since the dawn of recorded history, and probably even before, men and women have been grasping at the mechanisms by which they themselves exist. Only relatively recently, did this grasp yield anything of substance, and only within the last several decades did the proteins play a pivotal role in this existence. In this expose on the topic of protein structure some of the current issues in this scientific field are discussed. The aim is that a non-expert can gain some appreciation for the intricacies involved, and in the current state of affairs. The expert meanwhile, we hope, can gain a deeper understanding of the topic.

Download For Free

Bioinformatics - Trends and Methodologies....project Ideas

Bioinformatics - Trends and Methodologies is a collection of different views on most recent topics and basic concepts in bioinformatics. This book suits young researchers who seek basic fundamentals of bioinformatic skills such as data mining, data integration, sequence analysis and gene expression analysis as well as scientists who are interested in current research in computational biology and bioinformatics including next generation sequencing, transcriptional analysis and drug design. Because of the rapid development of new technologies in molecular biology, new bioinformatic techniques emerge accordingly to keep the pace of in silico development of life science. This book focuses partly on such new techniques and their applications in biomedical science. These techniques maybe useful in identification of some diseases and cellular disorders and narrow down the number of experiments required for medical diagnostic.

Download For Free

Easier Access to Bioinformatics Resources

BioInformatics Resource Inventory (B.I.R.I.)

The BioInformatics Resource Inventory (B.I.R.I.) is a public online searchable index of bioinformatics resources developed at the Biomedical Informatics Group. Information describing the resources has been automatically extracted from the literature and indexed using Natural Language and Text Mining techniques. The index is automatically updated by analyzing new papers describing existing resources (databases, tools, services…

The best part is that the team has made the new methodology available to everyone via a Web application called BioInformatics Resource Inventory (B.I.R.I.). BIRI allows the whole scientific community to search for bioinformatics resources by name, category, and domain.