Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

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...

Cancer Survival Analysis

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...

Cancers Originate from Somatic Mutations in a Single Cell

Cancers Originate from Somatic Mutations in a Single Cell

Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...

You might also read

Related Articles

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

Sort by

Same author

A sleep/wake circuit controls isoflurane sensitivity in Drosophila.

Current biology : CB·2013

Same author

Study of the impact of uterine artery embolization (UAE) on endometrial microvessel density (MVD) and angiogenesis.

Cardiovascular and interventional radiology·2013

Same author

Comparative proteomic analysis reveals differentially expressed proteins correlated with fuzz fiber initiation in diploid cotton (Gossypium arboreum L.).

Journal of proteomics·2013

Same author

Sodium intake from various time frames and incident hypertension among Chinese adults.

Epidemiology (Cambridge, Mass.)·2013

Same author

Spatial multi-scale variability of soil nutrients in relation to environmental factors in a typical agricultural region, eastern China.

The Science of the total environment·2013

Same author

Cleavage of metal-ion-induced DNAzymes released from nanolabels for highly sensitive and specific immunoassay.

Bioconjugate chemistry·2013

Search research articles

Related Experiment Video

Updated: Feb 18, 2026

Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies

Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies

Published on: September 15, 2023

LinkedOmics: analyzing multi-omics data within and across 32 cancer types.

Suhas V Vasaikar^1,2, Peter Straub³, Jing Wang^1,2

¹Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA.

Nucleic Acids Research

|November 15, 2017

Summary

LinkedOmics integrates multi-omics and clinical data for 32 cancer types, enabling comprehensive analysis of over a billion data points. This platform facilitates exploration, comparison, and biological interpretation of cancer data for researchers.

More Related Videos

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

Related Experiment Videos

Last Updated: Feb 18, 2026

Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies

Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies

Published on: September 15, 2023

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

Area of Science:

Bioinformatics
Cancer Genomics
Proteomics

Background:

The Cancer Genome Atlas (TCGA) project has generated extensive multi-omics data for numerous cancer types.
Integrating diverse datasets, including proteomics from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), presents a significant analytical challenge.
A unified platform is needed to effectively analyze and interpret these large-scale cancer datasets.

Purpose of the Study:

To develop and present LinkedOmics, a web application for comprehensive analysis of multi-omics and clinical data.
To provide tools for exploring associations, comparing findings, and interpreting biological insights from cancer data.
To establish a unique resource for biologists and clinicians studying cancer within and across tumor types.

Main Methods:

Development of the LinkedOmics web application with three integrated analysis modules: LinkFinder, LinkCompare, and LinkInterpreter.
LinkFinder enables exploration of associations between molecular or clinical attributes across billions of data points.
LinkCompare facilitates comparison of associations, particularly for multi-omics and pan-cancer studies, while LinkInterpreter performs pathway and network analysis for biological interpretation.

Main Results:

LinkedOmics successfully integrates multi-omics data (genomics, proteomics) and clinical data for 11,158 patients across 32 cancer types.
The platform hosts over a billion data points, offering extensive analytical capabilities.
Five case studies demonstrate the utility of LinkedOmics in accessing, analyzing, and comparing cancer multi-omics data.

Conclusions:

LinkedOmics provides a powerful and unique platform for cancer multi-omics data analysis and interpretation.
The integrated analysis modules enable researchers to uncover complex associations and gain biological understanding.
LinkedOmics serves as a valuable resource for advancing cancer research and clinical applications.