Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

19.1K
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%...
19.1K
DNA Microarrays02:34

DNA Microarrays

21.9K
Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
21.9K
Gene Families01:57

Gene Families

4.0K
4.0K
Gene Families01:57

Gene Families

10.2K
Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
10.2K
Genomics02:02

Genomics

41.5K
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...
41.5K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

16.5K
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...
16.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

DAQplugin: Deep Learning based Real-time Model Evaluation Plugin for ChimeraX.

bioRxiv : the preprint server for biology·2026
Same author

Direct Detection and Atomic Modeling of Ligands in Cryo-EM Maps Using Deep Learning.

bioRxiv : the preprint server for biology·2026
Same author

On the state of protein function prediction: a report on the fourth CAFA challenge.

bioRxiv : the preprint server for biology·2026
Same author

PL-PatchSurfer3: improved structure-based virtual screening for structure variation using 3D Zernike descriptors.

Journal of cheminformatics·2026
Same author

Multivalent recognition of ferritin by full-length NCOA4 enables robust ferritinophagy.

Protein science : a publication of the Protein Society·2026
Same author

MVGFormer: Multi-view perspective with graph-guided transformer for cryo-ET segmentation.

Knowledge-based systems·2026
Same journal

Correction: A method for supervoxel-wise association studies of age and other non-imaging variables from coronary computed tomography angiograms.

Scientific reports·2026
Same journal

Poly(bromophenol blue)/CoSn(OH)<sub>6</sub> cubic particles modified pencil graphite electrode for electrochemical determination of diphenhydramine.

Scientific reports·2026
Same journal

Dietary Chlorella, Spirulina, and acidifier modulate jejunal cytokine-related gene expression in broiler chickens.

Scientific reports·2026
Same journal

Perceived physical activity barriers in university students: associations with fatigue and eating behaviours.

Scientific reports·2026
Same journal

Refuge limitation structures habitat use in agricultural landscapes: evidence from Sunda pangolins.

Scientific reports·2026
Same journal

Lightweight stateless transaction verification with outsourced witness updates for UTXO blockchains.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Mar 16, 2026

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

10.6K

Missing gene identification using functional coherence scores.

Meghana Chitale1, Ishita K Khan1, Daisuke Kihara1,2

  • 1Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA.

Scientific Reports
|August 25, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method to identify missing genes in metabolic pathways by integrating gene expression, phylogenetic profiles, and novel function association scores like CAS and PAS. The approach significantly enhances accuracy in pathway reconstruction, particularly in yeast.

More Related Videos

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

47.1K
An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

4.1K

Related Experiment Videos

Last Updated: Mar 16, 2026

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

10.6K
Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

47.1K
An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

4.1K

Area of Science:

  • Bioinformatics
  • Systems Biology
  • Genomics

Background:

  • Genome sequence interpretation relies on reconstructing metabolic and signaling pathways.
  • Pathway reconstruction is hindered by missing gene information due to incomplete organismal data.
  • Identifying these missing genes is crucial for accurate pathway interpretation.

Purpose of the Study:

  • To develop an improved computational method for identifying missing genes in biological pathways.
  • To enhance the accuracy of pathway reconstruction by integrating diverse data sources.
  • To validate the method's effectiveness using the yeast enzyme-enzyme network.

Main Methods:

  • Developed a novel gene-finding method integrating gene expression, phylogenetic profiles, and function association scores.
  • Incorporated Co-occurrence Association Score (CAS) and PubMed Association Score (PAS) to assess functional coherence between candidate genes and network neighbors.
  • Utilized a network-topology-based weighting scheme to consider indirect neighbors in the analysis.

Main Results:

  • The integration of CAS and PAS significantly improved the accuracy of identifying missing genes compared to using only gene expression and phylogenetic profiles.
  • The method demonstrated substantial accuracy gains in reconstructing the yeast enzyme-enzyme network.
  • Considering indirect neighbors through network topology further enhanced the identification accuracy.

Conclusions:

  • The developed method effectively addresses the challenge of missing genes in pathway reconstruction.
  • Function association scores (CAS, PAS) and network topology are vital for improving gene identification accuracy.
  • This approach offers a more robust tool for interpreting genome sequences and understanding biological networks.