TA4b.2

SiGhS: A Statistical Method to Determine Significance of Biological Graph Differences

Whitney Sloneker, Brown University, United States; Lorin Crawford, Microsoft, Brown University, United States; Ritambhara Singh, Brown University, United States
Session:
TA4b: Information, Learning, and Genomics Lecture
Track:
Adaptive Systems, Machine Learning, and Data Analytics
Location:
Room 4
Presentation Time:
Tue, 27 Oct, 10:40 - 11:05 PT (UTC -7)
Session Co-Chairs:
Marco Mondelli, Institute of Science and Technology Austria (ISTA), Austria and Matthew Robinson, Institute of Science and Technology Austria (ISTA), Austria
Presentation
Discussion
Resources
No resources available.
Session TA4b
TA4b.1: Motif-preserving graph diffusion for small molecule drug design
Peizhi Niu, Shane Wang, Olgica Milenkovic, University of Illinois, Urbana-Champaign, United States
TA4b.2: SiGhS: A Statistical Method to Determine Significance of Biological Graph Differences
Whitney Sloneker, Brown University, United States; Lorin Crawford, Microsoft, Brown University, United States; Ritambhara Singh, Brown University, United States
TA4b.3: One-hot encoding captures non-linear genetic effects for plasma protein abundance
Kevin Kogler, Jakub Bajzik, Matthew Robinson, Marco Mondelli, Institute of Science and Technology Austria (ISTA), Austria
TA4b.4: Learning Population History from Genomic Data
Aditya Ravi, Joseph Liu, James O'Dwyer, Ilan Shomorony, University of Illinois Urbana-Champaign, United States
Contacts