Zobrazeno 1 - 10
of 160
pro vyhledávání: '"Tamer Kahveci"'
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 4, p 045016 (2024)
Understanding the genetic components of Alzheimer’s disease (AD) via transcriptome analysis often necessitates the use of invasive methods. This work focuses on overcoming the difficulties associated with the invasive process of collecting brain ti
Externí odkaz:
https://doaj.org/article/445d4afbf9ae4cda88b87426218fce02
Publikováno v:
BMC Genomics, Vol 21, Iss S9, Pp 1-3 (2020)
Externí odkaz:
https://doaj.org/article/e98519482e10464291296fe7eb7f6a4d
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S12, Pp 1-14 (2019)
Abstract Background Identification of motifs–recurrent and statistically significant patterns–in biological networks is the key to understand the design principles, and to infer governing mechanisms of biological systems. This, however, is a comp
Externí odkaz:
https://doaj.org/article/864cbc9af204431d9ae949acd89c03a7
Publikováno v:
BMC Genomics, Vol 20, Iss S6, Pp 1-16 (2019)
Abstract Background Biological networks describes the mechanisms which govern cellular functions. Temporal networks show how these networks evolve over time. Studying the temporal progression of network topologies is of utmost importance since it unc
Externí odkaz:
https://doaj.org/article/729aa197a2324d26a9d1b7fae999105b
Publikováno v:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-19 (2018)
Abstract Background Biological regulatory networks, representing the interactions between genes and their products, control almost every biological activity in the cell. Shortest path search is critical to apprehend the structure of these networks, a
Externí odkaz:
https://doaj.org/article/71f3ed0826d24531b38c33b8a97cc43b
Publikováno v:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-17 (2018)
Abstract Background Identifying motifs in biological networks is essential in uncovering key functions served by these networks. Finding non-overlapping motif instances is however a computationally challenging task. The fact that biological interacti
Externí odkaz:
https://doaj.org/article/2a94b03889974ea5a5cdc90fb0d31f44
Publikováno v:
BMC Bioinformatics, Vol 19, Iss S3, Pp 1-4 (2018)
Externí odkaz:
https://doaj.org/article/6f4d3596a7a446e1ad83fce6da571234
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S12, Pp 1-3 (2019)
Externí odkaz:
https://doaj.org/article/2879f5903b004134a90a9870eef01a0c
Publikováno v:
Cancer Informatics, Vol 2014, Iss Suppl. 3, Pp 15-31 (2014)
Externí odkaz:
https://doaj.org/article/d9de2ccbaa8548cfa3631649272497bc
Publikováno v:
PLoS ONE, Vol 11, Iss 9, p e0162173 (2016)
One of fundamental challenges in cancer studies is that varying molecular characteristics of different tumor types may lead to resistance to certain drugs. As a result, the same drug can lead to significantly different results in different types of c
Externí odkaz:
https://doaj.org/article/c0aaafa136da4aebb35790fa3ab54d1f