Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Archit Verma"'
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-25 (2024)
Abstract Genomics methods have uncovered patterns in a range of biological systems, but obscure important aspects of cell behavior: the shapes, relative locations, movement, and interactions of cells in space. Spatial technologies that collect genomi
Externí odkaz:
https://doaj.org/article/c47f14d9f2a2400c9f1dea624a803966
Autor:
Archit Verma, Barbara E. Engelhardt
Publikováno v:
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-15 (2020)
Abstract Background Modern developments in single-cell sequencing technologies enable broad insights into cellular state. Single-cell RNA sequencing (scRNA-seq) can be used to explore cell types, states, and developmental trajectories to broaden our
Externí odkaz:
https://doaj.org/article/90e627a3b7bb41bb90a6c2efc6e5c834
Autor:
Akshath Sharma, Sampann Arora, Pranav Chandramouli, Costas Varotsos, Sat Ghosh, Archit Verma, Ishan Saini
Publikováno v:
EnvironmentAsia, Vol 9, Iss 2, Pp 170-177 (2016)
A detailed microphysical characterization is presented for aerosol spectra over three major areas over Greece, namely- the Area West of Crete (AWC), the Greater Thessaloniki area (GTA) and the Greater Athens Area (GAA) based on measurements made by V
Externí odkaz:
https://doaj.org/article/6437a9cc469b4cdea1bee055e314c4ce
Autor:
Dr. Archit Verma
Background: Anterior cruciate ligament (ACL) and meniscal injuries pose significant challenges for individuals of all age groups. Arthroscopic reconstruction, utilizing hamstring tendon autografts, has emerged as an effective approach for restoring k
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02830cac5443f5bdf5708996a78db764
Publikováno v:
2021 IEEE Third International Conference on Cognitive Machine Intelligence (CogMI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2575d18c5880b9ef160201a61826f479
https://doi.org/10.1109/cogmi52975.2021.00033
https://doi.org/10.1109/cogmi52975.2021.00033
Autor:
Kazuhiro Aoki, Barbara E. Engelhardt, Danielle R. Isakov, Jared E. Toettcher, Archit Verma, Siddhartha G. Jena
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America
Significance Cells are under constant pressure to integrate information from both their environment and internal cellular processes. However, these effects often use the same signaling pathways, making autonomous and coupled signaling difficult to de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c08f3400ecbc47cd71211a88161c8092
https://doi.org/10.1073/pnas.2026123118
https://doi.org/10.1073/pnas.2026123118
Autor:
Lisa Schneper, Juan E. Castillo-Fernandez, Barbara E. Engelhardt, Isabella N. Grabski, Jordana T. Bell, Derek Aguiar, Sara McLanahan, Archit Verma, Daniel A. Notterman, De Vito R, Colter Mitchell
AO_SCPLOWBSTRACTC_SCPLOWThe Fragile Families Child Wellbeing Study (FFCWS) is a longitudinal cohort of ethnically diverse and primarily low socioeconomic status children and their families in the U.S. Here, we analyze DNA methylation data collected f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7473548a9e09a3d6423ca9084ffd0635
https://doi.org/10.1101/2021.05.20.444959
https://doi.org/10.1101/2021.05.20.444959
Autor:
Archit Verma, Barbara E. Engelhardt, Siddhartha G. Jena, Danielle R. Isakov, Kazuhiro Aoki, Jared E. Toettcher
Multi-cellular organisms rely on spatial signaling among cells to drive their organization, development, and response to stimuli. Several models have been proposed to capture the behavior of spatial signaling in multi-cellular systems, but existing a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e54d90f708981a88c0f67a2a0c0d08e4
https://doi.org/10.1101/2020.11.04.368001
https://doi.org/10.1101/2020.11.04.368001
Publikováno v:
CLOUD
Federated learning enables multiple, distributed participants (potentially on different clouds) to collaborate and train machine/deep learning models by sharing parameters/gradients. However, sharing gradients, instead of centralizing data, may not b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3446906a8ba3a3a19ae53a1b97d75aea
https://doi.org/10.1109/cloud49709.2020.00039
https://doi.org/10.1109/cloud49709.2020.00039
Autor:
Archit Verma, Barbara E. Engelhardt
Joint analysis of multiple single cell RNA-sequencing (scRNA-seq) data is confounded by technical batch effects across experiments, biological or environmental variability across cells, and different capture processes across sequencing platforms. Man
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3316e32a97544f46962f4dfde7ffc508