Summary of project PR001214
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001214. The data can be accessed directly via it's Project DOI: 10.21228/M8SH7V This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
| Project ID: | PR001214 |
| Project DOI: | doi: 10.21228/M8SH7V |
| Project Title: | Urine-Based Metabolomics and Machine Learning Reveals Metabolites Associated with Renal Cell Carcinoma Progression |
| Project Type: | multi-platform urine-based metabolomics |
| Project Summary: | Every year, hundreds of thousands of cases of renal carcinoma (RCC) are reported worldwide. Accurate staging of the disease is important for treatment and prognosis purposes; however, contemporary methods such as computerized tomography (CT) and biopsies are expensive and prone to sampling errors, respectively. As such, a non-invasive diagnostic assay for staging would be beneficial. This study aims to investigate urine metabolites as potential biomarkers to stage RCC. In the study, we identified a panel of such urine metabolites with machine learning techniques. |
| Institute: | University of Georgia |
| Department: | Biochemistry and Molecular Biology |
| Laboratory: | Fernandez Lab/ Edison Lab |
| Last Name: | Bifarin |
| First Name: | Olatomiwa |
| Address: | 315 Riverbend Rd, Athens, GA 30602 |
| Email: | olatomiwa.bifarin25@uga.edu |
| Phone: | (706) 542-4401 Lab: 1045 |
Summary of all studies in project PR001214
| Study ID | Study Title | Species | Institute | Analysis(* : Contains Untargted data) | Release Date | Version | Samples | Download(* : Contains raw data) |
|---|---|---|---|---|---|---|---|---|
| ST001923 | Urine-Based Metabolomics and Machine Learning Reveals Metabolites Associated with Renal Cell Carcinoma Progression | Homo sapiens | University of Georgia | MS* | 2021-10-18 | 1 | 82 | Uploaded data (15.6G)* |
| ST001924 | Urine-Based Metabolomics and Machine Learning Reveals Metabolites Associated with Renal Cell Carcinoma Progression NMR (part-I) | Homo sapiens | University of Georgia | NMR | 2021-10-18 | 1 | 84 | Uploaded data (330.1M)* |
