Zobrazeno 1 - 10
of 70
pro vyhledávání: '"Tayo Obafemi-Ajayi"'
Autor:
Philip J. Freda, Attri Ghosh, Priyanka Bhandary, Nicholas Matsumoto, Apurva S. Chitre, Jiayan Zhou, Molly A. Hall, Abraham A. Palmer, Tayo Obafemi-Ajayi, Jason H. Moore
Publikováno v:
BioData Mining, Vol 17, Iss 1, Pp 1-25 (2024)
Abstract Background The additive model of inheritance assumes that heterozygotes (Aa) are exactly intermediate in respect to homozygotes (AA and aa). While this model is commonly used in single-locus genetic association studies, significant deviation
Externí odkaz:
https://doaj.org/article/fdf760cf2d3745e7b3808633ce145e63
Publikováno v:
IEEE Access, Vol 12, Pp 42974-42991 (2024)
Cluster analysis has been applied to a wide range of problems as an exploratory tool to enhance knowledge discovery. Clustering aids disease subtyping, i.e. identifying homogeneous patient subgroups, in medical data. Missing data is a common problem
Externí odkaz:
https://doaj.org/article/227b37fc977042cfb3152d91974f3286
Autor:
Sasha Petrenko, Daniel B. Hier, Mary A. Bone, Tayo Obafemi-Ajayi, Erik J. Timpson, William E. Marsh, Michael Speight, Donald C. Wunsch
Publikováno v:
Information, Vol 15, Iss 3, p 125 (2024)
Biomedical datasets distill many mechanisms of human diseases, linking diseases to genes and phenotypes (signs and symptoms of disease), genetic mutations to altered protein structures, and altered proteins to changes in molecular functions and biolo
Externí odkaz:
https://doaj.org/article/5ccd300afced4175a4f3f09fd8436ed8
Autor:
John Matta, Daniel Dobrino, Dacosta Yeboah, Swade Howard, Yasser EL-Manzalawy, Tayo Obafemi-Ajayi
Publikováno v:
Frontiers in Human Neuroscience, Vol 16 (2022)
Autism Spectrum Disorder (ASD) is extremely heterogeneous clinically and genetically. There is a pressing need for a better understanding of the heterogeneity of ASD based on scientifically rigorous approaches centered on systematic evaluation of the
Externí odkaz:
https://doaj.org/article/460050ff72a342ffa09bef0611d2e6fb
Autor:
Daniel B. Hier, Tayo Obafemi-Ajayi, Matthew S. Thimgan, Gayla R. Olbricht, Sima Azizi, Blaine Allen, Bassam A. Hadi, Donald C. Wunsch
Publikováno v:
Biomarker Research, Vol 9, Iss 1, Pp 1-17 (2021)
Abstract Background The use of blood biomarkers after mild traumatic brain injury (mTBI) has been widely studied. We have identified eight unresolved issues related to the use of five commonly investigated blood biomarkers: neurofilament light chain,
Externí odkaz:
https://doaj.org/article/c5c8659cb7d449df818596860ad3dae7
Autor:
Dacosta Yeboah, Louis Steinmeister, Daniel B. Hier, Bassam Hadi, Donald C. Wunsch, Gayla R. Olbricht, Tayo Obafemi-Ajayi
Publikováno v:
IEEE Access, Vol 8, Pp 180690-180705 (2020)
We present a framework for an explainable and statistically validated ensemble clustering model applied to Traumatic Brain Injury (TBI). The objective of our analysis is to identify patient injury severity subgroups and key phenotypes that delineate
Externí odkaz:
https://doaj.org/article/e273e6bb7c4f48e19cd1682748569b82
Autor:
Sima Azizi, Daniel B. Hier, Blaine Allen, Tayo Obafemi-Ajayi, Gayla R. Olbricht, Matthew S. Thimgan, Donald C. Wunsch
Publikováno v:
Frontiers in Neurology, Vol 12 (2021)
Traumatic brain injury (TBI) imposes a significant economic and social burden. The diagnosis and prognosis of mild TBI, also called concussion, is challenging. Concussions are common among contact sport athletes. After a blow to the head, it is often
Externí odkaz:
https://doaj.org/article/2e3e71e79bc9410f9abf62a5f9128c35
Publikováno v:
Applied Network Science, Vol 3, Iss 1, Pp 1-22 (2018)
Abstract With the growing ubiquity of data in network form, clustering in the context of a network, represented as a graph, has become increasingly important. Clustering is a very useful data exploratory machine learning tool that allows us to make b
Externí odkaz:
https://doaj.org/article/0370aa271fd74f2a84515ba9ca59eb1f
Autor:
Mostafa Abbas, John Matta, Thanh Le, Halima Bensmail, Tayo Obafemi-Ajayi, Vasant Honavar, Yasser El-Manzalawy
Publikováno v:
PLoS ONE, Vol 14, Iss 11, p e0225382 (2019)
Reliable identification of Inflammatory biomarkers from metagenomics data is a promising direction for developing non-invasive, cost-effective, and rapid clinical tests for early diagnosis of IBD. We present an integrative approach to Network-Based B
Externí odkaz:
https://doaj.org/article/db2ca3303b1247ad82a68c7b9398a96b
Publikováno v:
Physical Review Research, Vol 3, Iss 1, p 013120 (2021)
This paper explores the benefit of added noise in increasing the computational complexity of digital recurrent neural networks (RNNs). The physically accepted model of the universe imposes rational number, stochastic limits on all calculations. An an
Externí odkaz:
https://doaj.org/article/cb7a153c73894841b67d7aa9388f83c5