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Ankit Agrawal (Ph.D.)
Ankit Agrawal (Ph.D.)
Lehrstuhl für Computational Biology of Spatial Biomedical Systems, Versbacher Str. 9, 97078 Würzburg
Verified email at uni-wuerzburg.de - Homepage
Title
Cited by
Cited by
Year
Quantifying randomness in protein–protein interaction networks of different species: a random matrix approach
A Agrawal, C Sarkar, SK Dwivedi, N Dhasmana, S Jalan
Physica A: Statistical Mechanics and its Applications 404, 359-367, 2014
262014
Nonequilibrium biophysical processes influence the large-scale architecture of the cell nucleus
A Agrawal, N Ganai, S Sengupta, GI Menon
Biophysical journal 118 (9), 2229-2244, 2020
222020
Chromatin as active matter
A Agrawal, N Ganai, S Sengupta, GI Menon
Journal of Statistical Mechanics: Theory and Experiment 2017 (1), 014001, 2017
192017
The inconvenience of data of convenience: computational research beyond post-mortem analyses
CA Azencott, T Aittokallio, S Roy, T Norman, S Friend, G Stolovitzky, ...
Nature methods 14 (10), 937-938, 2017
132017
Application of 3D MAPs pipeline identifies the morphological sequence chondrocytes undergo and the regulatory role of GDF5 in this process
S Rubin, A Agrawal, J Stegmaier, S Krief, N Felsenthal, J Svorai, Y Addadi, ...
Nature communications 12 (1), 5363, 2021
112021
THiCweed: fast, sensitive detection of sequence features by clustering big datasets
A Agrawal, SV Sambare, L Narlikar, R Siddharthan
Nucleic acids research 46 (5), e29-e29, 2018
62018
3D MAPs discovers the morphological sequence chondrocytes undergo in the growth plate and the regulatory role of GDF5 in this process
S Rubin, A Agrawal, J Stegmaier, J Svorai, Y Addadi, P Villoutreix, T Stern, ...
bioRxiv, 2020.07. 28.225409, 2020
12020
Nuclear Architecture from Chromosomes to Motifs
A Agrawal
HOMI BHABHA NATIONAL INSTITUTE, 2019
2019
Nuclear Architecture from Chromosomes to Motifs [HBNI Th158]
A Agrawal
The Institute of Mathematical Sciences, 2019
2019
A First-principles Approach to Large-scale Nuclear Architecture
A Agrawal, N Ganai, S Sengupta, GI Menon
Biophysical Journal 114 (3), 444a-445a, 2018
2018
THiCweed: fast, sensitive detection of sequence features by clustering big data sets Supplementary information
A Agrawal, SV Sambare, L Narlikar, R Siddharthan
2017
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Articles 1–11