Year: 2023
Type: article
Abstract: Clinical heterogeneity remains a challenge in the practice of medicine and is an underlying motivation for much of biomedical research. Unfortunately, despite an abundance of technologies capable of producing millions of discrete data elements with information about a patient's health status or disease prognosis, our ability to translate those data into meaningful improvements in understanding of clinical heterogeneity is limited. To address this gap, we have applied newer approaches to manifold learning and developed additional and complementary techniques to interrogate and interpret complex, high dimensional omics data. The central premise is that there exist manifolds embedded in high dimensional data that represent fundamental biologic processes that may help address the challenges of clinical heterogeneity. Preliminary evidence from several real-world data sets suggests that these techniques can identify coherent and reproducible manifolds embedded in higher dimensional omics data. Work is currently ongoing to determine the clinical informativeness of these novel data structures.
Source: PubMed Central
Authors: David Herrington, Yue Wang
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Awards: G1261793039, MESA, G1276754516, G1412221515, G1539384734, G1640378483, G1803853571, Wake Forest Clinical and Translational Science Award, G2144938473, G22458031, MESA, G2432076436, G2580996367, MESA, G2837638605, G290884426, G291913881, SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--EBCT READING, G3093995152, G3570589137, G3676546685, MESA, G3990748671, G4086764833, Development of COMBInatorial BIOmarkers for subclinical atherosclerosis, OPTION 3. 4/1/2014 - 3/31/2015. MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA) - READING CENTER, NHLBI, MESA, G5108002584, G514410172, SUBCLINICAL CARDIOVASCULAR DISEASE STUDY-ULTRASOUND, G5654179670, Metabolomic Signatures of CAD Associated Genotypes, Genomic and Proteomic Architecture of Atherosclerosis, Institute for Clinical and Translational Research, MESA, G66341962, G6742279884, G6798586005, MESA, G7462069030, Clinical and Translational Science Award, G842756795, G8761005068, G8852914737, G9000004549, G9000004784, G9000006353, G9000017360, G9000019818, G9000025517, G9000065698, Diabetes Research Center (DRC), UCLA Clinical and Translational Science Institute, G991334795
OpenAlex ID: W4386704590