Abstract Motivation Combination therapies have emerged as a treatment strategy for cancers to reduce the probability of drug resistance and improve outcomes. Large databases curating results many screening studies on preclinical cancer cell lines been developed, capturing synergistic antagonistic effects combination drugs in different lines. However, due high cost experiments sheer size possible combinations, these are quite sparse. This necessitates development transductive computational...

Understanding an enzyme's function is one of the most crucial problem domains in computational biology. Enzymes are a key component all organisms and many industrial processes as they help fighting diseases speed up essential chemical reactions. They have wide applications therefore, discovery new enzymatic proteins can accelerate biological research commercial productivity. Biological experiments, to determine function, time-consuming resource expensive.In this study, we propose novel...

Enzymes are critical proteins in every organism. They speed up essential chemical reactions, help fight diseases, and have a wide use the pharmaceutical manufacturing industries. Wet lab experiments to figure out an enzyme's function time consuming expensive. Therefore, need for computational approaches address this problem becoming necessary. Usually, enzyme is extremely specific performing its function. However, there exist enzymes that can perform multiple functions. A multi-functional...

Abstract Motivation Combination therapies have emerged as a treatment strategy for cancers to reduce the probability of drug resistance and improve outcome. Large databases curating results many screening studies on preclinical cancer cell lines been developed, capturing synergistic antagonistic effects combination drugs in different lines. However, due high cost experiments sheer size possible combinations, these are quite sparse. This necessitates development transductive computational...