Výsledky vyhledávání - "Yue W. Webster"

Supplementary Materials and Methods from Aurora A–Selective Inhibitor LY3295668 Leads to Dominant Mitotic Arrest, Apoptosis in Cancer Cells, and Shows Potent Preclinical Antitumor Efficacy

Supplementary Materials and Methods

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04ab9e588f7270d239b69faebcc24e90
https://doi.org/10.1158/1535-7163.22506969.v1

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Data from Aurora A–Selective Inhibitor LY3295668 Leads to Dominant Mitotic Arrest, Apoptosis in Cancer Cells, and Shows Potent Preclinical Antitumor Efficacy

Although Aurora A, B, and C kinases share high sequence similarity, especially within the kinase domain, they function distinctly in cell-cycle progression. Aurora A depletion primarily leads to mitotic spindle formation defects and consequently prom

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0aca539a9e32036f4566410352eeff32
https://doi.org/10.1158/1535-7163.c.6538536.v1

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Supplementary Tables from Aurora A–Selective Inhibitor LY3295668 Leads to Dominant Mitotic Arrest, Apoptosis in Cancer Cells, and Shows Potent Preclinical Antitumor Efficacy

Supplementary Tables

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b687d979fb87e1752e656129b11b4a8
https://doi.org/10.1158/1535-7163.22506966

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Supplementary Figures from Aurora A–Selective Inhibitor LY3295668 Leads to Dominant Mitotic Arrest, Apoptosis in Cancer Cells, and Shows Potent Preclinical Antitumor Efficacy

Supplementary Figures

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9753ae2ef1911fad6be7d03eb93839c9
https://doi.org/10.1158/1535-7163.22506972.v1

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Abstract 2535: Enhanced gene expression of replication fork and other E2F targets genes is associated with sensitivity and, paradoxically, also with acquired drug resistance, to the Chk1 inhibitor prexasertib

Autor: Wayne D. Blosser, Jack A. Dempsey, Ann M. McNulty, Wenjuan Wu, Philip J. Ebert, Jason C. Ting, Yue W. Webster, Trent R. Stewart, Xueqian Gong, Farhana F. Merzoug, Sean Buchanan, Ricardo Martinez

Publikováno v: Cancer Research. 79:2535-2535

Many cancers are under replicative stress (RS) arising from the combined influence of oncogenic drivers (i.e. Cyclin E, E2F, Myc), genomic instability and/or deficiencies in DNA Damage Repair (DDR). Tumors survive RS by upregulating checkpoints such

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::316d88953d1159264fd93e3e8cc5e5f1
https://doi.org/10.1158/1538-7445.am2019-2535

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AN ONTOLOGY FOR SEMANTIC INTEGRATION OF LIFE SCIENCE WEB DATABASES

Autor: Zina Ben Miled, Yue W. Webster, Nianhua Li, Yang Liu

Publikováno v: International Journal of Cooperative Information Systems. 12:275-294

The incompatibilities among complex data formats and various schema used by biological databases that house these data are becoming a bottleneck in biological research. For example, biological data format varies from simple words (e.g. gene name), nu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d5ef9cd8582ed3446fb1ff9d78aeedbf
https://doi.org/10.1142/s0218843003000747

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A framework for cross-disciplinary hypothesis generation

Autor: Yue W. Webster, Jacob Koehler, Ranga Chandra Gudivada, Mathew J. Palakal, Ernst R. Dow

Publikováno v: SAC

The complexity of cross-disciplinary knowledge discovery is two-fold: integration of vast amount of information in disparate silos, and dissemination of discovery to stakeholders with different interests. Here we propose a framework that combines Sem

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3fc450d913953825a5cde735f2151d86
https://doi.org/10.1145/1774088.1774414

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Leveraging health social networking communities in translational research

Autor: Jacob Koehler, Yue W. Webster, Ranga Chandra Gudivada, Mathew J. Palakal, Ernst R. Dow

Publikováno v: Journal of Biomedical Informatics. (4):536-544

Health social networking communities are emerging resources for translational research. We have designed and implemented a framework called HyGen, which combines Semantic Web technologies, graph algorithms and user profiling to discover and prioritiz

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2fd17882ce417571608d5be74c6a4c3a

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