CHAPTER ONE

INTRODUCTION

The term in silico was coined in 1989 as allusion to the Latin Phrases in-viro, in-vitro and in-situ which are commonly used in biology.

          In silico studies refers to the studies, facts, findings or experiment done in living organisms (i.e. the medicinal plant species) outside living organism (computer system)  and where they are found in nature respectively.

          The expression in silico was first used in public in 1989 in the workshop “Cellular Automata”: Theory and Application in Los Alamos New Mexico by Pedro Miramontes a Mathematician from National Autonomous University of Mexico (UNAM) who presented the report “DNA and RNA physiochemical constraints, Cellular Automata and Molecular Evolution;

          Mitochondrial and Plastid genomes show a wide array of architectures i.e. (make up) varying immensely in size, structures and content. Some organelle DNA’s have even developed elaborate eccentricities such as scrambled coding regions, non-standard genetic codes and convoluted modes of post-transcriptional modification and editing. Here we compare and contrast the breadth of genomic complexity between mitochondrial and plastid chromosomes.

          However, the complexity and intensity of genomic embellishments are consistently more pronounced for mitochondria than for plastids even when they are found in both compartments. We explore the evolutionary forces responsible for these patterns and argue the organelles DNA repair processes, mutation rates and population genetic landscapes are all important factors leading to the observed consequence and divergence in organelle genome architecture.

          Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data. As an interdisciplinary field of science, bioinformatics combines Computer Science, Biology, Mathematics and Engineering to analyze and interpret biological data.

          Bioinformatics has been used for in silico analyses of biological genes using mathematical and statistical techniques. More broadly, Bioinformatics is applied statistics and computing to biological science.

          Bioinformatics has become an important part of many areas of biology. In experimental molecular biology, Bioinformatics techniques such as image and signal processing allow extraction of useful results from large amount of raw data. In the field of genetics and genomics, it aids in sequencing and annotating genomes and their observed mutations. It plays a role in the text miming of biological literature and the development of biological and gene ontologies to organize and query biological data. It also plays a role in the analysis of gene and protein expression and regulation. Bioinformatics tools aid in the comparison of genetic and genomic data and more generally in the understanding of evolutionary aspects of molecular biology. At a more integrative level, it helps to analyze and catalogue the biological pathways and networks that are an important part of systems biology. In structural biology, it aids in the simulation and modeling of DNA, RNA, proteins as well as biomolecular interactions.

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