Zobrazeno 1 - 10
of 213
pro vyhledávání: '"M. Norden"'
Publikováno v:
mAbs, Vol 16, Iss 1 (2024)
Specificity profiling is a requirement for monoclonal antibodies (mAbs) and antibody-directed biotherapeutics such as CAR-T cells prior to initiating human trials. However, traditional approaches to assess the specificity of mAbs, primarily tissue cr
Externí odkaz:
https://doaj.org/article/e71bd051d23e4748a5db97586af61d16
Autor:
Stanislav Listopad, Christophe Magnan, Le Z Day, Aliya Asghar, Andrew Stolz, John A Tayek, Zhang-Xu Liu, Jon M Jacobs, Timothy R Morgan, Trina M Norden-Krichmar
Publikováno v:
PLOS Digital Health, Vol 3, Iss 2, p e0000447 (2024)
Distinguishing between alcohol-associated hepatitis (AH) and alcohol-associated cirrhosis (AC) remains a diagnostic challenge. In this study, we used machine learning with transcriptomics and proteomics data from liver tissue and peripheral mononucle
Externí odkaz:
https://doaj.org/article/70c69694d50b4a10aa033ee82af3e165
Autor:
Stanislav Listopad, Christophe Magnan, Aliya Asghar, Andrew Stolz, John A. Tayek, Zhang-Xu Liu, Timothy R. Morgan, Trina M. Norden-Krichmar
Publikováno v:
JHEP Reports, Vol 4, Iss 10, Pp 100560- (2022)
Background & Aims: Liver disease carries significant healthcare burden and frequently requires a combination of blood tests, imaging, and invasive liver biopsy to diagnose. Distinguishing between inflammatory liver diseases, which may have similar cl
Externí odkaz:
https://doaj.org/article/a8c226faa38c42908eda30464d20226b
Autor:
Josepmaria Argemi, Komal Kedia, Marina A. Gritsenko, Ana Clemente-Sanchez, Aliya Asghar, Jose M. Herranz, Zhang-Xu Liu, Stephen R. Atkinson, Richard D. Smith, Trina M. Norden-Krichmar, Le Z. Day, Andrew Stolz, John A. Tayek, Ramon Bataller, Timothy R. Morgan, Jon M. Jacobs
Publikováno v:
The American Journal of Pathology. 192:1658-1669
Alcohol-associated hepatitis (AH) is a form of liver failure with high short-term mortality. Recent studies have shown that defective function of hepatocyte nuclear factor 4 alpha (HNF4a) and systemic inflammation are major disease drivers of AH. Pla
Autor:
C. Schurmann, Stefan Konigorski, M. Norden, Marius Kloft, Christoph Lippert, C. Meltendorf, Matthias Kirchler
Publikováno v:
Bioinformatics. 38:3621-3628
Motivation Medical images can provide rich information about diseases and their biology. However, investigating their association with genetic variation requires non-standard methods. We propose transferGWAS, a novel approach to perform genome-wide a
Publikováno v:
MethodsX, Vol 2, Iss C, Pp 53-58 (2015)
The C26 adenocarcinoma tumor line is frequently used to establish peripheral tumors in mice for the study of cancer cachexia and cancer-related fatigue. Recently, we have noticed a progressive decline in the effects of tumor growth on our biological
Externí odkaz:
https://doaj.org/article/bac0cce5db754cefad173baed72e24fb
Autor:
Rachel McFarland Lucia, Xiyue Liao, Wei-Lin Huang, Danielle Forman, Alexis Kim, Argyrios Ziogas, Trina M. Norden-Krichmar, Deborah Goodman, Andrea Alvarez, Irene Masunaka, Khyatiben Pathak, Marissa McGilvrey, Victoria David-Dirgo, Apurva Hegde, Patrick Pirrotte, Hannah Lui Park
Publikováno v:
Cancer Research. 83:4222-4222
Background: Animal and epidemiologic studies suggest that exposure to the weed killer, glyphosate, and its primary metabolite aminomethylphosphonic acid (AMPA), is associated with increased risk for cancer, including breast cancer and non-Hodgkin's l
Autor:
Rachel M. Lucia, Wei-Lin Huang, Khyatiben V. Pathak, Marissa McGilvrey, Victoria David-Dirgo, Andrea Alvarez, Deborah Goodman, Irene Masunaka, Andrew O. Odegaard, Argyrios Ziogas, Patrick Pirrotte, Trina M. Norden-Krichmar, Hannah Lui Park
Publikováno v:
Environmental Health Perspectives. 130
Glyphosate is the most commonly used herbicide in the world and is purported to have a variety of health effects, including endocrine disruption and an elevated risk of several types of cancer. Blood DNA methylation has been shown to be associated wi
Publikováno v:
BMC bioinformatics, vol 23, iss 1
BMC Bioinformatics
BMC Bioinformatics, Vol 23, Iss 1, Pp 1-18 (2022)
BMC Bioinformatics
BMC Bioinformatics, Vol 23, Iss 1, Pp 1-18 (2022)
BackgroundA limitation of traditional differential expression analysis on small datasets involves the possibility of false positives and false negatives due to sample variation. Considering the recent advances in deep learning (DL) based models, we w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ec3437bc9b4ebc769347e3e4d4d442f
https://escholarship.org/uc/item/15t7k0r9
https://escholarship.org/uc/item/15t7k0r9
Publikováno v:
BMC Bioinformatics, Vol 20, Iss 1, Pp 1-10 (2019)
BMC Bioinformatics
BMC Bioinformatics
Background Researchers commonly analyze lists of differentially expressed entities (DEEs), such as differentially expressed genes (DEGs), differentially expressed proteins (DEPs), and differentially methylated positions/regions (DMPs/DMRs), across mu