2A. Day 1: Introduction to bioinformatics - bioinfokushwaha/Livestock_Genomics GitHub Wiki

Bioinformatics : An Impulsive or Contemplative Science

Bioinformatics is an interdisciplinary field of science that develops methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses computational, statistical, and computer programming techniques for computer simulation to understand the biological queries, which include development and use of specific analysis "pipelines" to explore gene structure and function, sequence variation (SNPs). These pipelines are used to better understand the genetic basis of disease, unique adaptations, desirable properties (esp. in agricultural species), or differences between populations.

Relationship Between Bioinformatics and Omics Technology

Integration of Bioinformatics: Bioinformatics is crucial for the analysis of the vast amount of data generated by omics technologies, which profile the transcriptome, genome, and other molecular characteristics (1 2 ).

Handling Complex Data: Omics technologies require computational analysis to handle extremely complex biological samples in large quantities with high sensitivity and specificity, which is accomplished through bioinformatics (3 ).

Biomedical Innovation: Omics technologies, supported by bioinformatics, offer the promise of monitoring, preventing, and treating age-related disabilities and diseases. This illustrates the vital role of bioinformatics in advancing our understanding of human aging through omics (4 5 ).

Advancing Methodological Development: Bioinformatics has played a crucial role in the rapid development of omics technologies, such as high-throughput sequencing and mass spectrometry, by enabling the systematic interrogation of cellular systems and the discovery of various molecular and regulatory mechanisms (6 7 ).

Omics technologies generate vast amounts of data from different biological samples, such as genomics profiling DNA, transcriptomics measuring transcripts, and proteomics quantifying proteins, among others (8 9 ). To manage this complexity, bioinformatics tools and techniques are essential to process, analyze, and interpret the large quantities of data produced by omics technologies. Bioinformatics enables the handling of extremely complex biological samples in large quantities with high sensitivity and specificity, allowing researchers to extract meaningful insights from the data generated by omics technologies. Therefore, integration of omics data is essential to combine the complementary knowledge brought by each omics layer. This integration aims to understand the interplay of molecules and the complex biology systematically and holistically (10 ).