kerepesi
Institute for Computer Science and Control (SZTAKI), Eötvös Loránd University, Budapest, HungaryHungary
Pinned Repositories
aging_ml
Prediction and characterization of human ageing-related proteins by using machine learning. Related publication: https://doi.org/10.1038/s41598-018-22240-w
AmphoraVizu
Chart visualization for metagenomics analysis tools AMPHORA2 and AmphoraNet. Related publication: http://dx.doi.org/10.1007/s00248-014-0502-6
Brain-Graph-Tools
Tools for data mining of brain graphs. Related publication: http://dx.doi.org/10.1007/s11571-017-9445-1
CE_m6A_analysis
IntersectionClock
MiStImm
MiStImm: an agent-based simulation tool to study the self-nonself discrimination of the adaptive immune response
MouseAgingClocks
Workflows for measuring epigenetic age of mouse RRBS samples. Genomic and rDNA epigenetic aging clock.
translocatome_ml
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.
kerepesi's Repositories
kerepesi/Brain-Graph-Tools
Tools for data mining of brain graphs. Related publication: http://dx.doi.org/10.1007/s11571-017-9445-1
kerepesi/MiStImm
MiStImm: an agent-based simulation tool to study the self-nonself discrimination of the adaptive immune response
kerepesi/MouseAgingClocks
Workflows for measuring epigenetic age of mouse RRBS samples. Genomic and rDNA epigenetic aging clock.
kerepesi/aging_ml
Prediction and characterization of human ageing-related proteins by using machine learning. Related publication: https://doi.org/10.1038/s41598-018-22240-w
kerepesi/IntersectionClock
kerepesi/AmphoraVizu
Chart visualization for metagenomics analysis tools AMPHORA2 and AmphoraNet. Related publication: http://dx.doi.org/10.1007/s00248-014-0502-6
kerepesi/CE_m6A_analysis
kerepesi/translocatome_ml
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.