Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Ali Oskooei"'
Autor:
Jannis Born, Matteo Manica, Ali Oskooei, Joris Cadow, Greta Markert, María Rodríguez Martínez
Publikováno v:
iScience, Vol 24, Iss 4, Pp 102269- (2021)
Summary: With the advent of deep generative models in computational chemistry, in-silico drug design is undergoing an unprecedented transformation. Although deep learning approaches have shown potential in generating compounds with desired chemical p
Externí odkaz:
https://doaj.org/article/2878649a15784acc80e2b1f5cc274279
Publikováno v:
2021 International Conference on Data Mining Workshops (ICDMW).
Autor:
Ali Oskooei, Joris Cadow, Matteo Manica, Greta Markert, Jannis Born, María Rodríguez Martínez
Publikováno v:
iScience, Vol 24, Iss 4, Pp 102269-(2021)
iScience, 24 (4)
iScience, 24 (4)
With the advent of deep generative models in computational chemistry, in-silico drug design is undergoing an unprecedented transformation. Although deep learning approaches have shown potential in generating compounds with desired chemical properties
Autor:
Ali Oskooei, Jonas R. Weiss, Sophie Mai Chau, Arvind Sridhar, Bruno Michel, María Rodríguez Martínez
Publikováno v:
Explainable AI in Healthcare and Medicine ISBN: 9783030533519
In this work we perform a study of various unsupervised methods to identify mental stress in firefighter trainees based on unlabeled heart rate variability data. We collect RR interval time series data from nearly 100 firefighter trainees that partic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a7d26589e0454b0a54fe480d4759a27
https://doi.org/10.1007/978-3-030-53352-6_9
https://doi.org/10.1007/978-3-030-53352-6_9
Autor:
Jannis, Born, Matteo, Manica, Ali, Oskooei, Joris, Cadow, Greta, Markert, María, Rodríguez Martínez
Publikováno v:
iScience
Summary With the advent of deep generative models in computational chemistry, in-silico drug design is undergoing an unprecedented transformation. Although deep learning approaches have shown potential in generating compounds with desired chemical pr
Publikováno v:
Nucleic Acids Research
Nucleic Acids Research, 48 (W1)
Nucleic Acids Research, 48 (W1)
The identification of new targeted and personalized therapies for cancer requires the fast and accurate assessment of the drug efficacy of potential compounds against a particular biomolecular sample. It has been suggested that the integration of com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81b6bfcdb935bed13a6675c5c639ecdf
https://zenodo.org/record/3935564
https://zenodo.org/record/3935564
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030452568
RECOMB
RECOMB
The pharmaceutical industry has experienced a significant productivity decline: Less than 0.01% of drug candidates obtain market approval, with an estimated 10–15 years until market release and costs that range between one [2] to three billion doll
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::01b0e3e95d74a61eb522ed9ca20c8498
https://doi.org/10.1007/978-3-030-45257-5_18
https://doi.org/10.1007/978-3-030-45257-5_18
Publikováno v:
Chemical Reviews
Chemical Reviews, 118 (4)
Chemical Reviews, 118 (4)
Hydrodynamic phenomena are ubiquitous in living organisms and can be used to manipulate cells or emulate physiological microenvironments experienced in vivo. Hydrodynamic effects influence multiple cellular properties and processes, including cell mo
Autor:
Ali Oskooei, Govind V. Kaigala
Publikováno v:
IEEE Transactions on Biomedical Engineering. 64:1261-1269
We present a method for nonintrusive localization and reagent delivery on immersed biological samples with topographical variation on the order of hundreds of micrometers. Our technique, which we refer to as the deep-reaching hydrodynamic flow confin