Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Vahid Rezaei Tabar"'
Publikováno v:
Arthritis Research & Therapy, Vol 22, Iss 1, Pp 1-12 (2020)
Abstract Background A comprehensive intuition of the systemic lupus erythematosus (SLE), as a complex and multifactorial disease, is a biological challenge. Dealing with this challenge needs employing sophisticated bioinformatics algorithms to discov
Externí odkaz:
https://doaj.org/article/96cc14e70efb4b6fb0ca7aff2e11e500
Publikováno v:
BMC Genomics, Vol 20, Iss 1, Pp 1-13 (2019)
Abstract Background Machine learning can effectively nominate novel genes for various research purposes in the laboratory. On a genome-wide scale, we implemented multiple databases and algorithms to predict and prioritize the human aging genes (PPHAG
Externí odkaz:
https://doaj.org/article/2207731695f1480dabdd105fdeac78de
Autor:
Vahid Rezaei Tabar, Fatemeh Elahi
Publikováno v:
Applied Artificial Intelligence, Vol 32, Iss 2, Pp 214-227 (2018)
A good method of combining Bayesian networks (BNs) should be a generic one that ensures a combined BN meets three important criteria of avoiding cycles, preserving conditional independencies, and preserving the characteristics of individual BN parame
Externí odkaz:
https://doaj.org/article/c23cc9ade2e241bbab52b262808bea6b
Autor:
Paulina Urban, Nirmal Das, Subhadip Basu, Michał Denkiewicz, Dariusz Plewczynski, Vahid Rezaei Tabar, Grzegorz Bokota
Publikováno v:
J Comput Biol
The dendritic spines play a crucial role in learning and memory processes, epileptogenesis, drug addiction, and postinjury recovery. The shape of the dendritic spine is a morphological key to understand learning and memory process. The classification
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3946427ad6355a2cb08b1f99338c6691
https://doi.org/10.1089/cmb.2019.0383
https://doi.org/10.1089/cmb.2019.0383
Autor:
Ivan Radovanovic, R. Wu, Paul Kongkham, Hubert Rehrauer, Jason E. Fish, S. Suntharalingham, S. Vetiska, H. Zhong, Luca Regli, D. Rodrigues Rodrigues, Peter Carmeliet, S. Takada, Martin E. Schwab, Thomas Wälchli, Karl Frei, Gelareh Zadeh, Karl Lothard Schaller, K. Yu, Gary D. Bader, Mark Bernstein, Vahid Rezaei Tabar, Moheb Ghobrial, Taufik A. Valiante, F. Farnhammer, Philippe P. Monnier, Troy Ketela, Peter B. Dirks, Ralph Schlapbach, K. De Bock, Jeroen Bisschop, Mario-Luca Suvà
A broad range of brain pathologies critically relies on the vasculature, and cerebrovascular disease is a leading cause of death worldwide. However, the cellular and molecular architecture of the human brain vasculature remains poorly understood. Her
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d62ad683d25c9445c56defba67f098e6
https://doi.org/10.1101/2021.10.18.464715
https://doi.org/10.1101/2021.10.18.464715
Publikováno v:
Statistical Analysis and Data Mining: The ASA Data Science Journal. 12:394-403
One hypothetically well‐founded approach for learning a Directed Acyclic Graph (DAG) is to utilize the Markov Chain Monte Carlo (MCMC) techniques. In the MCMC, the uniform noninformative p...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c2f2cccd8dc040172549bb8cbbe0e0a
https://doi.org/10.1002/sam.11430
https://doi.org/10.1002/sam.11430
Publikováno v:
Journal of Statistical Computation and Simulation. 89:1957-1970
The aim of this paper is learning directed acyclic graph (DAG) by determination of candidate causes for each discrete variable. Based on the fact that the candidate causes of a variable must be a s...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::65fd3865154465ee5f2e2ab7331c5566
https://doi.org/10.1080/00949655.2019.1604709
https://doi.org/10.1080/00949655.2019.1604709
Publikováno v:
Medical journal of the Islamic Republic of Iran. 35
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f451ab0150328c98d989bd5c3b3d2893
https://pubmed.ncbi.nlm.nih.gov/35321377
https://pubmed.ncbi.nlm.nih.gov/35321377
MotivationOne of the most popular techniques in biological studies for analyzing high throughput data is pathway enrichment analysis (PEA). Many researchers apply the existing methods without considering the topology of pathways or at least they have
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af971040cec6aff6b03fbccfe8d0fb1c
https://doi.org/10.1101/2020.01.13.905448
https://doi.org/10.1101/2020.01.13.905448
Publikováno v:
Pattern Recognition Letters. 111:23-29
One of the most effective structure-learning methods in a Bayesian network is the K2 algorithm. Because the performance of the K2 algorithm depends on the node ordering, more effective node ordering inference methods are needed. In this paper, we int
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ca2462aa9aa2e7889b82994d8641a20
https://doi.org/10.1016/j.patrec.2018.04.019
https://doi.org/10.1016/j.patrec.2018.04.019