Supplemental Tables S1 and S2 for Combining structural modeling and deep learning to calculate the E. coli protein interactome and functional networks by Diana Murray (16859046)

“…The integrated method has better performance and identifies more high-confidence interactions than any of the component methods. The AF3Complex algorithm was used to predict the structures of 374 PPIs with a large fraction having at least partially overlapping interfaces with PrePPI models of the same complex. …”

Data Sheet 1_Antibodies and cryptographic hash functions: quantifying the specificity paradox.pdf by Robert J. Petrella (5146220)

“…In addition, an antibody-epitope interaction probability model is used to help show how newly formed antibodies may avoid cross-reactivity with self-antigens despite their high degree of multispecificity and how the requirement of polyclonal binding likely improves the overall specificity of the immune response. …”

Data Sheet 2_Antibodies and cryptographic hash functions: quantifying the specificity paradox.pdf by Robert J. Petrella (5146220)

“…In addition, an antibody-epitope interaction probability model is used to help show how newly formed antibodies may avoid cross-reactivity with self-antigens despite their high degree of multispecificity and how the requirement of polyclonal binding likely improves the overall specificity of the immune response. …”