Multi-granular modeling: the chase for hidden cancer mechanisms
Advisor Information
Hesham Ali
Location
UNO Criss Library, Room 232
Presentation Type
Oral Presentation
Start Date
2-3-2018 9:15 AM
End Date
2-3-2018 9:30 AM
Abstract
Modern biomedical research instruments have promised higher accuracy and precision. Further, data integration from these data were supposed to bring us an era of biomedical progress. However, overparsimoniousness and novel data sensitivities have left much research projects inert. For the past few years, we have developed knowledge of granularity and other integration sensitivities. Now our research focuses on just how far a granularity-aware data integration project can take cancer research. Using 182 TCGA RNA-Seq samples, we have constructed a multi-granularity model which allows us to examine potential cancer mechanisms at in high detail.
Multi-granular modeling: the chase for hidden cancer mechanisms
UNO Criss Library, Room 232
Modern biomedical research instruments have promised higher accuracy and precision. Further, data integration from these data were supposed to bring us an era of biomedical progress. However, overparsimoniousness and novel data sensitivities have left much research projects inert. For the past few years, we have developed knowledge of granularity and other integration sensitivities. Now our research focuses on just how far a granularity-aware data integration project can take cancer research. Using 182 TCGA RNA-Seq samples, we have constructed a multi-granularity model which allows us to examine potential cancer mechanisms at in high detail.