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Genome Annotation and Assembly

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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...

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Related Experiment Video

Updated: Feb 21, 2026

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Federation in genomics pipelines: techniques and challenges.

Somali Chaterji¹, Jinkyu Koo², Ninghui Li¹

¹Computer Science, Purdue University, Indiana, USA.

Briefings in Bioinformatics

|October 3, 2017

Summary

Federating computational resources and datastores is crucial for bioinformatics portals. This approach enables efficient data processing without large-scale data transfers, supporting growing user bases and data volumes.

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Area of Science:

Bioinformatics
Distributed Cyberinfrastructures
Computational Resource Management

Background:

Federation is widely used for distributed cyberinfrastructures, unifying resources from multiple organizations.
Current bioinformatics federation primarily focuses on datastores, limiting its potential.
Increasing data volumes and processing demands in fields like genomics necessitate broader federation.

Purpose of the Study:

To advocate for and demonstrate the importance of federating both computational resources (CPU, GPU, FPGA) and datastores in bioinformatics.
To address the challenges of scaling bioinformatics portals to meet growing user and data demands.
To share insights and tools for federating bioinformatics infrastructures, exemplified by the metagenomics-RAST (MG-RAST) pipeline.

Main Methods:

Proposing a model for federating both computational resources and datastores.
Developing and applying computational tools for infrastructure federation.
Illustrating the federation process through the metagenomics-RAST (MG-RAST) pipeline, a widely used metagenomics analysis tool.

Main Results:

Identified key computational tools essential for federating bioinformatics infrastructures.
Highlighted open research challenges in implementing federated bioinformatics systems.
Demonstrated a phased approach to federating the MG-RAST pipeline without disrupting its 50,000 annual users.

Conclusions:

Federating both computational resources and datastores is vital for the scalability and efficiency of bioinformatics portals.
Successful federation requires careful planning to avoid service disruption for existing users.
This work aims to encourage wider adoption of federated bioinformatics infrastructures to support scientific advancement.