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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.

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...

lncRNA - Long Non-coding RNAs

lncRNA - Long Non-coding RNAs

In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...

lncRNA - Long Non-coding RNAs

lncRNA - Long Non-coding RNAs

Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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ncFN: a comprehensive non-coding RNA function annotation framework based on a global and heterogeneous biomolecular

Min Long¹, Haizhou Liu^2,3, Mengqin Yuan¹

¹Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 211106, China.

Non-Coding RNA Research

|October 27, 2025

Summary

We developed ncFN, a novel framework for annotating non-coding RNA (ncRNA) functions using a global biomolecular network. This tool accurately identifies functions for microRNAs, long non-coding RNAs, and circular RNAs.

Keywords:

Biological network Function annotation Molecular interaction Random walk with restart ncRNA

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RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA

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Published on: April 10, 2018

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Non-coding RNAs (ncRNAs) play crucial roles in biological processes, but their functions remain largely uncharacterized.
Existing methods often focus on single ncRNA types, limiting comprehensive functional annotation.

Purpose of the Study:

To develop ncFN, a novel and comprehensive framework for ncRNA function annotation.
To integrate diverse ncRNA types (miRNAs, lncRNAs, circRNAs) into a unified analytical approach.

Main Methods:

Construction of a Global Interaction Network (GIN) integrating ncRNA-ncRNA, ncRNA-protein coding gene (PCG), and PCG-PCG interactions.
Quantification of Association Strengths (ASs) using Random Walk with Restart.
Functional annotation via Gene Set Enrichment Analysis.

Main Results:

ncFN successfully annotated functions for a large number of ncRNAs across diverse types.
The framework demonstrated superior performance compared to conventional methods, especially for disease-relevant ncRNAs.
ncFN facilitates enrichment analysis for multiple ncRNAs or pathways.

Conclusions:

ncFN is a comprehensive and reliable tool for functional annotation of miRNAs, lncRNAs, and circRNAs.
The framework is suitable for widespread application in ncRNA research.
ncFN is publicly accessible, promoting collaborative research.