Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Tunca Doğan"'
Autor:
Heval Atas Guvenilir, Tunca Doğan
Publikováno v:
Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-36 (2023)
Abstract The identification of drug/compound–target interactions (DTIs) constitutes the basis of drug discovery, for which computational predictive approaches have been developed. As a relatively new data-driven paradigm, proteochemometric (PCM) mo
Externí odkaz:
https://doaj.org/article/c6682b1be6c2439097c1459f640060f5
Autor:
Fatma Cankara, Tunca Doğan
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 4743-4758 (2023)
Background: Genomic variations may cause deleterious effects on protein functionality and perturb biological processes. Elucidating the effects of variations is critical for developing novel treatment strategies for diseases of genetic origin. Comput
Externí odkaz:
https://doaj.org/article/d9acbe9b594d4b2e863104bc44be4cbc
Publikováno v:
Machine Learning: Science and Technology, Vol 4, Iss 2, p 025035 (2023)
Automated computational analysis of the vast chemical space is critical for numerous fields of research such as drug discovery and material science. Representation learning techniques have recently been employed with the primary objective of generati
Externí odkaz:
https://doaj.org/article/637ede00a8164e5e97ed8eb34b854e8c
Publikováno v:
Frontiers in Molecular Biosciences, Vol 8 (2021)
Externí odkaz:
https://doaj.org/article/2b4f2edd96194ac09f76315adad196e0
Autor:
Tunca Doğan, Ece Akhan Güzelcan, Marcus Baumann, Altay Koyas, Heval Atas, Ian R Baxendale, Maria Martin, Rengul Cetin-Atalay
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 11, p e1009171 (2021)
Predictive approaches such as virtual screening have been used in drug discovery with the objective of reducing developmental time and costs. Current machine learning and network-based approaches have issues related to generalization, usability, or m
Externí odkaz:
https://doaj.org/article/300998f38bfd495a97aea9c262e40130
Autor:
Alperen Dalkiran, Ahmet Sureyya Rifaioglu, Maria Jesus Martin, Rengul Cetin-Atalay, Volkan Atalay, Tunca Doğan
Publikováno v:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-13 (2018)
Abstract Background The automated prediction of the enzymatic functions of uncharacterized proteins is a crucial topic in bioinformatics. Although several methods and tools have been proposed to classify enzymes, most of these studies are limited to
Externí odkaz:
https://doaj.org/article/b99d8a4b09534f78a2529ea118214ae3
Autor:
Tunca Doğan
Publikováno v:
PeerJ, Vol 6, p e5298 (2018)
Analysing the relationships between biomolecules and the genetic diseases is a highly active area of research, where the aim is to identify the genes and their products that cause a particular disease due to functional changes originated from mutatio
Externí odkaz:
https://doaj.org/article/cb7c296894c3424fb29f13cdc0a0c06c
Autor:
Tunca Doğan, Bilge Karaçalı
Publikováno v:
PLoS ONE, Vol 8, Iss 9, p e75458 (2013)
Identifying shared sequence segments along amino acid sequences generally requires a collection of closely related proteins, most often curated manually from the sequence datasets to suit the purpose at hand. Currently developed statistical methods a
Externí odkaz:
https://doaj.org/article/284f83eec0db416899e3080a1922d44f
Autor:
A Samet Özdilek, Ahmet Atakan, Gökhan Özsarı, Aybar Acar, M Volkan Atalay, Tunca Doğan, Ahmet S Rifaioğlu
Publikováno v:
Briefings in Bioinformatics. 24
As the number of protein sequences increases in biological databases, computational methods are required to provide accurate functional annotation with high coverage. Although several machine learning methods have been proposed for this purpose, ther
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e72be65ea74df0f7914ba8085ed51ee4
https://doi.org/10.1093/bib/bbac627
https://doi.org/10.1093/bib/bbac627
Autor:
Rengul Cetin-Atalay, Deniz Cansen Kahraman, Esra Nalbat, Ahmet Sureyya Rifaioglu, Ahmet Atakan, Ataberk Donmez, Heval Atas, M. Volkan Atalay, Aybar C. Acar, Tunca Doğan
Publikováno v:
Journal of Gastrointestinal Cancer. 52:1266-1276
Computational approaches have been used at different stages of drug development with the purpose of decreasing the time and cost of conventional experimental procedures. Lately, techniques mainly developed and applied in the field of artificial intel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb538c74d54630c9ecfc554e50ef4b31
https://doi.org/10.1007/s12029-021-00768-x
https://doi.org/10.1007/s12029-021-00768-x