Bioinformatics Applications in Biotechnology

Why Bioinformatics? Since the sequencing of the first complete microbial genome of Haemophilus influenzae in 1995, hundreds of microbial genomes have been sequenced and archived for public research in GenBank.

The vast amount of data generated by genome sequencing projects is becoming unmanageable

Bioinformatics has silently filled in the role of cost effective data analysis.

bioinformatics analysis has enhanced our understandings about the genome structure and the microorganism restructuring process.  

Where Bioinformatics tools is applicable?

Microbial genome applications Molecular medicine Personalized medicine Preventative medicine Gene therapy Drug development Antibiotic resistance Evolutionary studies Waste cleanup

Climate change Studies  Alternative energy sources  Crop improvement Forensic analysis Insect resistance Improve nutritional quality  Development of Drought resistant varieties Vetinary Science

How bioinformatics tools will help you?

Two major fields

1. Development of computational tools and databases

• Software for sequence analysis• Software for structural analysis• Software for functional analysis• Construction and curation of biological databases

2. Generate biological knowledge to better understand living systems•Often identify new problems that require new software to analyze

Working with Genome

Analysis of genome data Analysis of protein sequences Prediction of promoter and coding regions

Identification of gene and gene functions

Bioinformatics programs such as GLIMMER and GenBank are used to identify the coding region in the genome

Annotate structure and function of genes

Three-dimensional (3D) Structure Modeling

Protein and nucleic acid structural analysis Comparison Classification Prediction

Drug DiscoveryReduce the cost and time of Drug Discovery

To improve drug discovery we need efficient Bioinformatics algorithms and approaches for

• Target Identification• Target validation• Lead Identification• Lead Optimization

Next Generation Sequencing (NGS) Data Analysis

Increase in data due to high throughput next generation sequencing methodsImportant to make sense of data, associate data for implicationsResearchers are comfortable with NGS technology but not data interpretation and bioinformatics: a bottle neck

Where NGS Data analysis can be applied?

Differential Expression Analysis

To understand the molecular basis of phenotypic biology especially during disease Expression levels during different set of conditions NutrigenomicsPersonalized medicine

Chip-Seq Analysis

Protein DNA InteractionHigh resolution mapping of the protein-DNA binding loci that are important in understanding of process in development and disease

Metagenomics Data Analysis

Metagenomics provides access to the functional gene composition of microbial communities and gives a much broader description Analyze genetic content of entire communities of organisms

Eg: Discovery of AmmoniaOxidizing Archaea

Small and miRNA sequence Analysis

miRNAs are short, non coding RNAs that have the capacity to bind, capture and silence hundreds of genes with and across diverse signaling pathways

The Bioinformatics MarketThe global bioinformatics market is estimated to reach $13.3 billion by 2020. Factors for growth :1] Increasing government initiatives and funding, 2] Growing use of bioinformatics in drug discovery and biomarkers development The Hindrance :1] Factors such as dearth of skilled personnel to ensure proper use of bioinformatics tools, and 2] lack of integration of a wide variety of data generated through various bioinformatics platforms

We at RASA work towards closing this bridge between Bio and IT

THANK YOU