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Sanjib Das

Researcher at Jadavpur University

Publications -  18
Citations -  138

Sanjib Das is an academic researcher from Jadavpur University. The author has contributed to research in topics: Pentanoic Acids & Computer animation. The author has an hindex of 6, co-authored 18 publications receiving 84 citations. Previous affiliations of Sanjib Das include Advanced Materials and Processes Research Institute & Indian Institute of Technology Guwahati.

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Journal ArticleDOI

Inhibitors of gelatinases (MMP-2 and MMP-9) for the management of hematological malignancies.

TL;DR: In this paper, a review of clinical trials of matrix metalloproteinases (MMPs) for advanced stage solid tumor cancers is presented, which can therefore act as a learning experience for future development of successful gelatinase inhibitors for the management of hematological malignancies.
Journal ArticleDOI

Remote Communication Engineering Experiments Through Internet

TL;DR: This remote laboratory system aims at providing an opportunity to students from distant places to conduct hardware experiments but also to take the corresponding measurements, and uses real-time capture of images and data from the instruments to perform experiment-related measurements.
Book ChapterDOI

Determination of Urbanization Impact on Rain Water Quality with the Help of Water Quality Index and Urbanization Index

TL;DR: In this article, the influence of urbanization on quality of rain water in Kolkata was analyzed with the help of the relationship between water quality index (WQI) and urbanization index (UI) of the sampling location.
Journal ArticleDOI

Synthesis, anticancer activity, structure-activity relationship and binding mode of interaction studies of substituted pentanoic acids.

TL;DR: Compounds 18 and 31 were found to induce apoptosis effectively in a dose-dependent fashion in Jurkat-E6.1 cell line and may be useful to battle against cancer.
Proceedings ArticleDOI

Development of an Assamese OCR using Bangla OCR

TL;DR: The development of an OCR for the Assamese language by modifying an existing O CR for the Bangla language, which incorporates a two stage recognizer using SVM classifier with no post-processing.