N
Nitin Agarwal
Researcher at University of Arkansas at Little Rock
Publications - 314
Citations - 4199
Nitin Agarwal is an academic researcher from University of Arkansas at Little Rock. The author has contributed to research in topics: Social media & Computer science. The author has an hindex of 29, co-authored 259 publications receiving 3651 citations. Previous affiliations of Nitin Agarwal include University College of Medical Sciences & University of Miami.
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Proceedings ArticleDOI
Identifying the influential bloggers in a community
TL;DR: The challenges of identifying influential bloggers are discussed, what constitutes influential bloggers is investigated, a preliminary model attempting to quantify an influential blogger is presented, and the way for building a robust model that allows for finding various types of the influentials is paved.
Journal ArticleDOI
PTEN, NHERF1 and PHLPP form a tumor suppressor network that is disabled in glioblastoma.
Jennifer R. Molina,Nitin Agarwal,Fabiana C. Morales,Yuho Hayashi,Kenneth Aldape,Gilbert J. Cote,Maria-Magdalena Georgescu,Maria-Magdalena Georgescu +7 more
TL;DR: It is shown here that PTEN modulates the PI3K-Akt pathway in glioblastoma within a tumor suppressor network that includes Na+/H+ exchanger regulatory factor 1 (NHERF1) and pleckstrin-homology domain leucine-rich repeat protein phosphatases 1 (PHLPP1).
Journal ArticleDOI
Blogosphere: research issues, tools, and applications
Nitin Agarwal,Huan Liu +1 more
TL;DR: Various state-of-the-art research issues are introduced, some key elements of research such as tools and methodologies in Blogosphere are reviewed, and a case study of identifying the influential bloggers in a community is presented to exemplify the integration of some major aspects discussed in this paper.
Journal ArticleDOI
Topic taxonomy adaptation for group profiling
TL;DR: This article addresses the problem of how to adapt a topic taxonomy to the accumulated data that reflects the change of a group's interest to achieve dynamic group profiling, and presents a viable algorithm that can efficiently accomplish taxonomy adaptation.
Journal ArticleDOI
Proteomic Analysis of Cellular Response to Osmotic Stress in Thick Ascending Limb of Henle’s Loop (TALH) Cells
TL;DR: TALH cells exhibiting low or high levels of resistance to osmotic stress were characterized using proteomic tools and many other metabolic enzymes like glutathione S-transferase, malate dehydrogenase, lactate dehydrationase, α enolase, glyceraldehyde-3-phosphate dehydrogensase, and triose-Phosphate isomerase were up-regulated.