Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Charles Bergeron"'
Microelectrode arrays (MEA) hold great promise for a broad range of applications that require reliable characterization of the growth and function of neurons in culture. Widespread adoption of this platform depends on analytical methods to extract me
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0d401bea1b9bf5976b0e5302fa475b3
https://doi.org/10.1101/2022.05.27.493606
https://doi.org/10.1101/2022.05.27.493606
Publikováno v:
Annals of the New York Academy of Sciences. 1387:112-123
Big Data is no longer solely the purview of big organizations with big resources. Today's routine tools and experimental methods can generate large slices of data. For example, high-throughput sequencing can quickly interrogate biological systems for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f40caaf87f854035bf92c4655d7e752
https://doi.org/10.1111/nyas.13281
https://doi.org/10.1111/nyas.13281
Autor:
Dustin Nabhan, Michael A. Cooper, John P. Vardiman, Russell Emmons, Charles Bergeron, William J. Moreau, Philip M. Gallagher, Jacob A. Siedlik
Publikováno v:
Journal of Athletic Training. 51:74-81
Context Analysis of injury and illness data collected at large international competitions provides the US Olympic Committee and the national governing bodies for each sport with information to best prepare for future competitions. Research in which a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef25abe09d3acc6e1a4929b7f4b1cbc3
https://doi.org/10.4085/1062-6050-51.2.02
https://doi.org/10.4085/1062-6050-51.2.02
Publikováno v:
Journal of Medicinal Chemistry
Treatment of ionization and tautomerism of ligands and receptors is one of the unresolved issues in structure-based prediction of binding affinities. Our solution utilizes the thermodynamic master equation, expressing the experimentally observed asso
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f8ad2b81a07e8ee2fd5b9aa46b3ffc1
http://europepmc.org/articles/PMC3315360
http://europepmc.org/articles/PMC3315360
Publikováno v:
Journal of Chemical Information and Modeling. 51:2808-2820
Least-squares fitting of the Hill equation to quantitative high-throughput screening (qHTS) assays results in frequent unsatisfactory fits. We learn and exploit prior knowledge to improve the Hill fitting in a nonlinear regression method called domai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::103797e989e5ae735f311d6a60beff30
https://doi.org/10.1021/ci200210d
https://doi.org/10.1021/ci200210d
Publikováno v:
Molecular Informatics. 30:765-777
Making suitable modeling choices is crucial for successful in silico drug design, and one of the most important of these is the proper extraction and curation of data from qHTS screens, and the use of optimized statistical learning methods to obtain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82a9dcc0d68960d1f9644dc0fc2079d9
https://doi.org/10.1002/minf.201100092
https://doi.org/10.1002/minf.201100092
Publikováno v:
Machine Learning. 85:175-208
This paper introduces two types of nonsmooth optimization methods for selecting model hyperparameters in primal SVM models based on cross-validation. Unlike common grid search approaches for model selection, these approaches are scalable both in the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ed836ccab011c8a1bbd89e88798039b
https://doi.org/10.1007/s10994-011-5246-7
https://doi.org/10.1007/s10994-011-5246-7
Publikováno v:
Engineering Applications of Artificial Intelligence. 18:973-983
This paper proposes a framework for the training of learning systems for regression when (i) the number of examples is small and contains interdependencies, and (ii) each sample consists of large quantities of discrete data that are functional in nat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::475d2788ab9d5953a439614098d08644
https://doi.org/10.1016/j.engappai.2005.03.006
https://doi.org/10.1016/j.engappai.2005.03.006
Publikováno v:
BMC Neuroscience
Multielectrode arrays (MEA) are broadly used for in vitro cell culture observation. Complete realization of this platform’s potential to the study of disease and development depends on the capability to make 1) reliable and repeatable observations,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::551180b2f7bbcb2fc3aad39dfe32d402
https://doi.org/10.1186/1471-2202-15-s1-p208
https://doi.org/10.1186/1471-2202-15-s1-p208
Publikováno v:
BMC Neuroscience
Multielectrode arrays (MEA) are routinely used to observe the development of neuronal networks in vitro, making simultaneous recordings of small proximal subpopulation activity within a cell culture. We propose the use of graph theoretic measures to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d3e60e0f8d21ef65add8f3696996a51
https://doi.org/10.1186/1471-2202-15-s1-p207
https://doi.org/10.1186/1471-2202-15-s1-p207