Drug target ontology to classify and integrate drug discovery data

Autor: Yu Lin, Saurabh Mehta, Hande Küçük-McGinty, John Paul Turner, Dusica Vidovic, Michele Forlin, Amar Koleti, Dac-Trung Nguyen, Lars Juhl Jensen, Rajarshi Guha, Stephen L. Mathias, Oleg Ursu, Vasileios Stathias, Jianbin Duan, Nooshin Nabizadeh, Caty Chung, Christopher Mader, Ubbo Visser, Jeremy J. Yang, Cristian G. Bologa, Tudor I. Oprea, Stephan C. Schürer

Publikováno v: Journal of Biomedical Semantics, Vol 8, Iss 1, Pp 1-16 (2017)

Abstract Background One of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant

Externí odkaz: https://doaj.org/article/c7f21332499a4a20a9198a03f5457353

Automatic tumor segmentation in single-spectral MRI using a texture-based and contour-based algorithm

Autor: Nooshin Nabizadeh, Miroslav Kubat

Publikováno v: Expert Systems with Applications. 77:1-10

We propose a new fully automatic method to detect and segment brain lesions.The method is based on a texture-based and a contour-based algorithm.The algorithm is independent of multi-spectral MRI, and local or global registration. Automatic detection

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::934f86afc450e02795da58bcab12445e
https://doi.org/10.1016/j.eswa.2017.01.036

Drug target ontology to classify and integrate drug discovery data

Autor: Dusica Vidovic, Cristian Bologa, Christopher Mader, Jeremy J. Yang, Stephan C. Schürer, Tudor I. Oprea, Vasileios Stathias, Lars Juhl Jensen, Stephen L. Mathias, Yu Lin, Hande Küçük-McGinty, Nooshin Nabizadeh, Saurabh Mehta, Oleg Ursu, Rajarshi Guha, Michele Forlin, Dac-Trung Nguyen, Ubbo Visser, Jianbin Duan, Amar Koleti, John Paul Turner, Caty Chung

Publikováno v: Lin, Y, Mehta, S, Küçük-McGinty, H, Turner, J P, Vidovic, D, Forlin, M, Koleti, A, Nguyen, D-T, Jensen, L J, Guha, R, Mathias, S L, Ursu, O, Stathias, V, Duan, J, Nabizadeh, N, Chung, C, Mader, C, Visser, U, Yang, J J, Bologa, C G, Oprea, T I & Schürer, S C 2017, ' Drug target ontology to classify and integrate drug discovery data ', Journal of Biomedical Semantics, vol. 8, no. 1, 50 . https://doi.org/10.1186/s13326-017-0161-x
Journal of Biomedical Semantics
Journal of Biomedical Semantics, Vol 8, Iss 1, Pp 1-16 (2017)

BackgroundOne of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a607e862d3e37df637108b26ea053b73
https://curis.ku.dk/portal/da/publications/drug-target-ontology-to-classify-and-integrate-drug-discovery-data(c8da5b40-158d-4821-9130-1662a4ef2cb7).html

Automatic tumor lesion detection and segmentation using modified winnow algorithm

Autor: Nooshin Nabizadeh, Miroslav Kubat, M. Dorodch

Publikováno v: ISBI

Automated recognition of brain tumors in magnetic resonance images (MRI) is a difficult procedure due to the variability and complexity of the location, size, shape, and texture of these lesions. Due to intensity similarities between brain lesions an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0971dababd96d51f0700f9a2770d8342
https://doi.org/10.1109/isbi.2015.7163819

Automatic tumor lesion detection and segmentation using histogram-based gravitational optimization algorithm

Autor: Mohsen Dorodchi, Nooshin Nabizadeh

Publikováno v: CIMSIVP

In this paper, an automated and customized brain tumor segmentation method is presented and validated against ground truth applying simulated T1-weighted magnetic resonance images in 25 subjects. A new intensity-based segmentation technique called hi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5791df2f0b254be93308ed56780b38c8
https://doi.org/10.1109/cimsivp.2014.7013271