kerepesi Goto Github PK
Name: Csaba Kerepesi
Type: User
Company: Institute for Computer Science and Control (SZTAKI), Eötvös Loránd University, Budapest, Hungary
Location: Hungary
Name: Csaba Kerepesi
Type: User
Company: Institute for Computer Science and Control (SZTAKI), Eötvös Loránd University, Budapest, Hungary
Location: Hungary
Prediction and characterization of human ageing-related proteins by using machine learning. Related publication: https://doi.org/10.1038/s41598-018-22240-w
Chart visualization for metagenomics analysis tools AMPHORA2 and AmphoraNet. Related publication: http://dx.doi.org/10.1007/s00248-014-0502-6
Tools for data mining of brain graphs. Related publication: http://dx.doi.org/10.1007/s11571-017-9445-1
MiStImm: an agent-based simulation tool to study the self-nonself discrimination of the adaptive immune response
Workflows for measuring epigenetic age of mouse RRBS samples. Genomic and rDNA epigenetic aging clock.
Translocatome is a novel resource for the analysis of protein translocation between cellular organelles. Using the gradient boosting machine learning tool, XGBoost, Translocatome provides translocation probability values for 13,066 human proteins identifying 1133 and 3268 high- and low-confidence translocating proteins, respectively.
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