An overview of advances in bioinformatics and its application in functional genomics

Bioinformatics is the scientific discipline that is concerned with the efficient management and useful interpretation of large scale biological information. Functional genomics aims at mapping DNA sequences and the components they encode for, to the function they perform. Initial efforts in bioinformatics were focused on the analysis of DNA sequence data. Presently, the scope and objectives of bioinformatics research and development have been broadened owing to the accelerating generation of data from various sources and for various cellular processes, the continuously evolving analytical technologies and the increasing computational capability. Bioinformatics offers an indispensable technology for function assignment and it has been used widely for gene annotation based on protein function predictions. However, as the sequence information is growing exponentially, the number of genes of unknown function is also growing, creating a challenge in the current computational approaches applied in bioinformatics. These limitations are being overcome through advances combining experimental and computational approaches, e.g. nanofabrication techniques. Despite the progress attained, analysis frameworks that could be used to analyze large data arising from signal transduction and biotransformation to provide quantitative predictions are inadequate. Trancriptome profiling is important because it provides information on the number of genes and their abundance in a tissue or given an induced condition e.g. diseased plants. Microarrays are hybridization experiments involving comparison of relative amounts of cellular mRNA from two tissue samples. Most of microarrays used in biological sciences can be divided into complementary DNA (cDNA) and oligonucleotide microarrays. The exploitation of hybridization in microarray analyses has sharply accelerated the search for defective genes of interest in both plants and animals. Microarrays provide the means to repeatedly measure the expression levels of a large number of genes at a time. Major limitations of this technology include decreased sensitivity of the arrays to the detection of genes with low expression levels and difficulties in data exchange due to the lack of standardization in platform fabrication, assay protocols and analysis methods.