Genomics Overview - Concepedia

Principles

Definition

Genomics is the interdisciplinary field of biology focused on the structure, function, evolution, mapping, and editing of genomes. It employs high-throughput technologies and computational approaches to comprehensively analyze the entire complement of genetic material within organisms, providing insights into biological systems, health, and disease.

Ontological type

Core Methods

Key Applications

Data Analysis Pipelines

Key developments

Key Figures

Foundational Genomic Methods era

Allan M. Maxam [1] was associated with Harvard University [3] and Tufts University [4] during the Foundational Genomic Methods era. He co-developed a new method for sequencing DNA [5], a breakthrough that established practical sequencing workflows foundational to reading genomes. Wendy V. Gilbert [2] worked with Harvard University [3] during this era. Her co-authorship of the 1977 paper A new method for sequencing DNA [5] helped accelerate sequencing capabilities that underpinned early genomic methods.

Reference and Comparative Genomics era

Eric S. Lander[1] is a central figure in the era of Reference and Comparative Genomics, with affiliations at Harvard University[3] and Massachusetts Institute of Technology[4] during 1986-2007. His contributions in this era include Gene set enrichment analysis[6], MAPMAKER[7], and The Structure of Haplotype Blocks in the Human Genome[8], which advanced genome-scale interpretation, enabled construction of reference linkage maps, and clarified haplotype architecture for cross-species comparison. David Botstein[2] is another pivotal figure in this era, with affiliations at Massachusetts Institute of Technology[4] and University of California, San Francisco[5] during 1986-2007. His papers include Gene Ontology: tool for the unification of biology[9], Cluster analysis and display of genome-wide expression patterns[10], and Comprehensive Identification of Cell Cycle–regulated Genes of the Yeast<i>Saccharomyces cerevisiae</i>by Microarray Hybridization[11], which established shared vocabularies, patterns, and gene sets that supported cross-dataset integration in this era.

Population-Scale Pan-Genomics era

Wolfgang Huber [1] is associated with Northwestern University [3] and Heidelberg University [4] in this era. His key contributions include the development and application of RNA-seq analysis methods such as DESeq2 [7] for moderated estimation of fold change and dispersion, and approaches for detecting differential usage of exons from RNA-seq data [8], which were pivotal for robust, scalable transcriptome analyses in population-scale genomics. Gordon K. Smyth [2] is associated with Université Paris Cité [5] and The University of Queensland [6] in this era. His notable contribution is featureCounts: an efficient general purpose program for assigning sequence reads to genomic features [9], enabling fast, scalable read counting that underpins large-scale analyses characteristic of population-scale pan-genomics.