Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Syeda Sakira Hassan"'
Autor:
Syeda Sakira Hassan, Simo Sarkka
Publikováno v:
IEEE Transactions on Automatic Control. :1-8
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1dd429d3419162e6d1f7e8d17a5e0ae1
https://doi.org/10.1109/tac.2023.3234236
https://doi.org/10.1109/tac.2023.3234236
We propose a novel classifier accuracy metric: the Bayesian Area Under the Receiver Operating Characteristic Curve (CBAUC). The method estimates the area under the ROC curve and is related to the recently proposed Bayesian Error Estimator. The metric
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45e8b707065149aefc067268bffa8fe8
Autor:
Syeda Sakira Hassan
Publikováno v:
Tampere University
Over recent years, data-intensive science has been playing an increasingly essential role in biological discovery and biomedical science. The explosion of information in biology poses challenges in organizing data, discovering relevant information fr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::40e909e1f289b15529490056d6b34f0e
Identification of feasible pathway information for c-di-GMP binding proteins in cellulose production
Publikováno v:
IFMBE Proceedings ISBN: 9789811051210
In this paper, we utilize a machine learning approach to identify the significant pathways for c-di-GMP signaling proteins. The dataset involves gene counts from 12 pathways and 5 essential c-di-GMP binding domains for 1024 bacterial genomes. Two nov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35b2ab3473611b05aa5ac693722ee187
https://doi.org/10.1007/978-981-10-5122-7_167
https://doi.org/10.1007/978-981-10-5122-7_167
Publikováno v:
Cancer Informatics, Vol 14s5 (2015)
Cancer Informatics
Cancer Informatics, Vol 2015, Iss Suppl. 5, Pp 75-85 (2016)
Cancer Informatics
Cancer Informatics, Vol 2015, Iss Suppl. 5, Pp 75-85 (2016)
In this paper, we study the problem of feature selection in cancer-related machine learning tasks. In particular, we study the accuracy and stability of different feature selection approaches within simplistic machine learning pipelines. Earlier stud
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60fe8ce8be7836003d5fcad705b57656
https://trepo.tuni.fi/handle/10024/99726
https://trepo.tuni.fi/handle/10024/99726
Publikováno v:
BMC Microbiology
Background Vibrio (V.) parahaemolyticus causes seafood-borne gastro-intestinal bacterial infections in humans worldwide. It is widely found in marine environments and is isolated frequently from seawater, estuarine waters, sediments and raw or insuff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6c376459fdf166d1d1ac53a763be2168
https://doi.org/10.1186/s12866-015-0565-7
https://doi.org/10.1186/s12866-015-0565-7
Publikováno v:
BMC Systems Biology
Background In bioprocess development, the needs of data analysis include (1) getting overview to existing data sets, (2) identifying primary control parameters, (3) determining a useful control direction, and (4) planning future experiments. In parti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d0d0ba11b2b7cc9027acf0fe8d29e942
http://europepmc.org/articles/PMC3750505
http://europepmc.org/articles/PMC3750505
Publikováno v:
BMC Microbiology; 10/23/2015, Vol. 15, p1-13, 13p