Drug combination therapy is a promising solution to many complicated diseases. Since
experimental measurements cannot be scaled to millions of candidate combinations, many …

For many multigene or multifactorial diseases, the one-drug therapy for inhibiting a defined
molecular target is often less effective than combined treatments. Typically, drug …

Building prediction models for outcomes of clinical relevance when only a limited number of
mutational features are available causes considerable challenges due to the sparseness …

Understanding the temporal dynamics of gene expression is crucial for developmental
biology, tumor biology, and biogerontology. However, some time points remain challenging …

Neurofibromatosis Type 1 (NF1) is one of the most common genetic tumor predisposition
syndromes, affecting up to 1 in 2500 individuals. Up to half of patients with NF1 develop …

This book provides information about different types and stages of cancer and their subtypes
with their respective molecular mechanisms, etiology, histopathology, and cellular origins …

Identifying effective therapeutic treatment strategies is a major challenge to improving
outcomes for patients with breast cancer. To gain a comprehensive understanding of how …

A strategy based on machine learning (ML) and deep learning has emerged as a time-and
cost-efficient way to explore the large combination space. This chapter begins with an …

Traditionally, optimization problems in operations research have been studied in a complete
information setting; the input/data is collected and made fully accessible to the user, before …

Essays on Network Theory: Diffusion, Link Analysis, and Hypergraph Learning Shatian Wang
Submitted in partial fulfillment of the Page 1 Essays on Network Theory: Diffusion, Link Analysis …