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Genomics

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

Next-generation Sequencing

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.

Sanger Sequencing

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...

Comparing Copy Number Variations and SNPs

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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Related Experiment Video

Updated: Jul 3, 2026

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Published on: September 20, 2024

AI in Genomics: From Variant Calling to Multi-Omics Integration.

Hina Sultana¹, Sabyasachi Mohanty², Abhishikt David Solomon³

¹Integrative Program in Biological and Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Bioessays : News and Reviews in Molecular, Cellular and Developmental Biology

|July 2, 2026

Summary

Artificial intelligence (AI) is revolutionizing genomics by enhancing variant calling, gene expression analysis, and CRISPR-Cas9 optimization. These AI strategies accelerate discovery in complex genomic data for precision medicine.

Related Experiment Videos

Last Updated: Jul 3, 2026

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Published on: September 20, 2024

Area of Science:

Genomics and Bioinformatics
Computational Biology
Genomic Technologies

Background:

Traditional statistical methods struggle with complex genomic patterns.
Genomic technologies generate vast, intricate datasets.
AI offers novel approaches to analyze and interpret genomic information.

Purpose of the Study:

To provide a concise overview of AI's transformative impact on major genomic technologies.
To highlight AI applications in variant calling, gene expression, single-cell transcriptomics, CRISPR-Cas9, and multi-omics integration.
To discuss current limitations and future directions for AI in genomics.

Main Methods:

Review of AI applications across key genomic technologies.
Analysis of machine learning for variant calling and RNA-Seq.
Exploration of deep learning in single-cell transcriptomics and CRISPR-Cas9 optimization.
Examination of AI in multi-omics data integration.

Main Results:

AI significantly improves accuracy and efficiency in variant calling and gene expression analysis.
Deep learning enhances single-cell transcriptomics analysis and CRISPR-Cas9 editing.
AI facilitates multi-omics integration for a comprehensive view of cellular regulation and disease.
AI addresses challenges like data sparsity, model bias, and privacy concerns.

Conclusions:

AI is an indispensable tool for unraveling genomic complexity.
AI accelerates the development and application of precision medicine.
Future directions include interpretable models, collaborative learning, and open science practices.