Bioinformatics is an integrative field of computer science, genetics, genomics, proteomics, and statistics, which has undoubtedly revolutionized the study of biology and medicine in past decades. It mainly assists in modeling, predicting and interpreting large multidimensional biological data by utilizing advanced computational methods. Despite its enormous potential, bioinformatics is not widely integrated into the academic curriculum as most life science students and researchers are still not equipped with the necessary knowledge to take advantage of this powerful tool. Hence, the primary purpose of our book is to supplement this unmet need by providing an easily accessible platform for students and researchers starting their career in life sciences. This book aims to avoid sophisticated computational algorithms and programming. Instead, it focuses on simple DIY analysis and interpretation of biological data with personal computers. Our belief is that once the beginners acquirethese basic skillsets, they will be able to handle most of the bioinformatics tools for their research work and to better understand their experimental outcomes.
Our second title of this volume set In Silico Life Sciences: Medicine provides hands-on experience in analyzing high throughput molecular data for the diagnosis, prognosis, and treatment of monogenic or polygenic human diseases. The key concepts in this volume include risk factor assessment, genetic tests and result interpretation, personalized medicine, and drug discovery. This volume is expected to train readers in both single and multi-dimensional biological analysis using open data sets, and provides a unique learning experience through clinical scenarios and case studies.

1. Driving forces of Bioinformatics

2. Genetic association from RFLPs to millions of variant markers - Unravelling the genetic complexity of diseases
3. Diagnostic revolution post-Human Genome Sequence project: High throughput technologies and Bioinformatics
4. Genomic revolution driven Cancer Research
5. Chromosomal Microarray in the New High Throughput Technological and Bioinformatic Era
6. Finding a Needle in a Haystack: Variant Effect Predictor (VEP) to Prioritize Candidate Variants from Millions
7. Clinical Strategies for Developing Next-Generation Cancer Precision Medicine
8. Dental stem cells in regenerative medicine: Emerging trends and prospects in the era of bioinformatics
9. Multiple Analyte Profiling Technology (xMAP) coupled with Functional Bioinformatics Strategies: Potential Applications in Protein Biomarker Profiling in Autoimmune Inflammatory Diseases
10. Design and Development of Small Molecules from Somatic, Stem Cell Reprogramming and Therapy
11.Molecular Modeling and drug design techniques in Microbial Drug Discovery
12
Combinatorial designing of novel lead molecules towards the putative drugs targets of extreme drug resistant Mycobacterium tuberculosis: a future insight for molecular medicine
Index.