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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...

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A Multi-Omics Extraction Method for the In-Depth Analysis of Synchronized Cultures of the Green Alga Chlamydomonas reinhardtii

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Symptom Science: Repurposing Existing Omics Data.

Nicole D Osier¹, Christopher C Imes¹, Heba Khalil²

¹1 School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA.

Biological Research for Nursing

|September 11, 2016

Summary

This summary is machine-generated.

Repurposing large omics and phenotype datasets can advance symptom science. Nurse scientists can analyze existing data to uncover biological underpinnings of symptoms like fatigue and pain without new participant recruitment.

Keywords:

big data omics repurposing symptoms

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Area of Science:

Biomedical research
Data science
Symptom science

Background:

Omics approaches (genomics, transcriptomics, proteomics, etc.) generate vast datasets.
These datasets remain valuable for secondary research after initial study aims are met.
Longitudinal epidemiological studies often collect rich phenotype data, including symptom information.

Purpose of the Study:

To introduce resources for repurposing omics data.
To provide guidance on utilizing these databases for symptom research.
To encourage the use of existing data to advance symptom science.

Main Methods:

Searching databases like dbGaP for omics and symptom data (e.g., cognitive impairment, fatigue, pain).
Leveraging existing longitudinal and epidemiological study data.
Analyzing large-scale datasets for ancillary investigations and hypothesis generation.

Main Results:

Numerous studies contain both omics and symptom data, particularly for common symptoms.
The Database of Genotypes and Phenotypes (dbGaP) is a key resource for symptom-related data.
Repurposing data enables analysis of symptom development and severity across thousands of individuals.

Conclusions:

Existing omics and phenotype data offer a powerful, cost-effective avenue for symptom science research.
Nurse scientists can investigate biological underpinnings of symptoms by analyzing large, publicly available datasets.
This approach facilitates hypothesis testing, replication, and mega-analyses in symptom research without new data generation.