Bioinformatics

A single remarkable breakthrough of the 21st century is likely to be biotechnology based on bioinformatics principles and algorithms. Bioinformatics is advanced by different disciplines. Much scientific, industrial, social, political, economic, and religious activity in upcoming years will be influenced by looming advancements in genetic research. Biostatisticians and computational biologists engaged in bioinformatics are working to clearly comprehend how molecular machinery works, fails, and can be repaired. One needs an excellent command of and expertise in biology, calculus, probability, mathematical statistics, and computer science to follow and make contributions in bioinformatics, an emerging discipline that analyzes large genetic data sets using statistical and information techniques. The discipline is growing quickly as a result of the rapid availability of DNA or protein sequence data on the World Wide Web. Because the biological machine is chance oriented, both probability and statistics are fundamental to understanding DNA or protein sequences.

Bioinformatics is one of three branches in a new discipline. The other two branches are medical informatics and health informatics. Medical informatics concentrates on computational algorithms to improve communication and understanding in order to manage medical knowledge and application. Microarray technology is the driving engine of this discipline. Health informatics studies the dynamics among (a) computers, communications, and other information sciences; (b) engineering, technology, and other sciences; and (c) medical research, education, and practice. Bioinformatics is a collection of tools and ideas for deciphering the complexity of molecular machinery. According to bioinformatics, biology is informational science, and this complex and diversified field is increasingly becoming a cross-disciplinary science. It is in its infancy but evolving rapidly. Biostatisticians, computer scientists, operations researchers, and molecular biologists work hard to enrich bioinformatics.

Since the discovery of the helix structure of DNA by James D. Watson and Francis H. C. Crick, several array-based biotechnologies have been constructed to determine and exploit gene expression levels and their interactions. Gene expression is a basic link between genotype and phenotype. Gene expression data are generated on a massive scale. New statistical principles and computing techniques are necessary to meet [Page 91]the demand for quick and correct interpretations of so much data.

As the territory of bioinformatics is changing dramatically, statisticians have to learn the language and jargon of bioinformatics. For example, much of the so-called simple random sampling, stratifications, randomization, replication, and so on, of the 20th century has become obsolete in the genetic research arena of the 21st century. DNA-oriented research ideas are geared to statistics' being an exact science.

John Naisbitt states in Megatrends that “we are drowning in information but starved of knowledge.” Fast-improving computing facilities change the way knowledge, discovery, and application in all scientific and day-to-day life are done. Before, genetic data were analyzed using a hypothesis-driven-reductions approach, but now, it is all done by a data-driven approach. Consequently, bioinformatics ideas play a significant role in genetic research.

Bioinformatics is all about identifying genes in genome sequences, figuring out closeness of one sequence to another, and answering questions such as the following: How similar are two different organisms? Where in DNA is a particular gene? What proteins are produced by a particular gene? What are the interrelations between genes and proteins? How are one person's genes different from those of another individual? And how can we design a way to store, process, and analyze this knowledge? Molecular human biology can be summarized as follows: There are 22 chromosomes in paired style. Every human female has two X chromosomes whereas a human male has one X and one Y chromosome. Each chromosome has a single double stranded DNA molecule with complementary nucleotides (A-T, G-C) forming pairs in the strands. The nucleotides are A for adenine, T for thymine, G for guanine, and C for cytosine. There may be redundant information in each strand. Organisms need to produce proteins for a variety of functions in life. There is a code for the start and end of the proteins. Major terms in bioinformatics include exon (segment of DNA that supplies information to make proteins), intron (a noncoding segment that interrupts exons to produce a proper copy of RNA), and splice site (the boundary of an exon and an intron). This site allows the uninterrupted gene or amino acid sequence of proteins. Promoter sites are segments of DNA that start the transcription of genes, enhancing controls of the transcription.

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