Quantifying label enrichment from two mass isotopomers increases proteome coverage for in vivo protein turnover using heavy water metabolic labeling

Autor: Henock M. Deberneh, Doaa R. Abdelrahman, Sunil K. Verma, Jennifer J. Linares, Andrew J. Murton, William K. Russell, Muge N. Kuyumcu-Martinez, Benjamin F. Miller, Rovshan G. Sadygov

Publikováno v: Communications Chemistry, Vol 6, Iss 1, Pp 1-12 (2023)

Abstract Heavy water metabolic labeling followed by liquid chromatography coupled with mass spectrometry is a powerful high throughput technique for measuring the turnover rates of individual proteins in vivo. The turnover rate is obtained from the e

Externí odkaz: https://doaj.org/article/2fd9fe96ab7f42029f30a4b802d31e12

POCS-based Clustering Algorithm

Autor: Le-Anh Tran, Henock M. Deberneh, Truong-Dong Do, Thanh-Dat Nguyen, My-Ha Le, Dong-Chul Park

A novel clustering technique based on the projection onto convex set (POCS) method, called POCS-based clustering algorithm, is proposed in this paper. The proposed POCS-based clustering algorithm exploits a parallel projection method of POCS to find

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c8a58ab1ca0fe34a7cd3af360ac1458f

Prediction of Type 2 Diabetes Based on Machine Learning Algorithm

Autor: Henock M. Deberneh, Intaek Kim

Publikováno v: International Journal of Environmental Research and Public Health
Volume 18
Issue 6
International Journal of Environmental Research and Public Health, Vol 18, Iss 3317, p 3317 (2021)

Prediction of type 2 diabetes (T2D) occurrence allows a person at risk to take actions that can prevent onset or delay the progression of the disease. In this study, we developed a machine learning (ML) model to predict T2D occurrence in the followin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::30e2b24c243ac007389dc1e06ba90785

Predicting Output Power for Nearshore Wave Energy Harvesting

Autor: Henock M. Deberneh, Intaek Kim

Publikováno v: Applied Sciences; Volume 8; Issue 4; Pages: 566
Applied Sciences, Vol 8, Iss 4, p 566 (2018)

Energy harvested from a Wave Energy Converter (WEC) varies greatly with the location of its installation. Determining an optimal location that can result in maximum output power is therefore critical. In this paper, we present a novel approach to pre

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::218aed2d0634883e08f3d7820e7d9951