AI Medical Compendium Journal:
Molecular bioSystems

Showing 11 to 19 of 19 articles

Gene essentiality prediction based on fractal features and machine learning.

Molecular bioSystems
Essential genes are required for the viability of an organism. Accurate and rapid identification of new essential genes is of substantial theoretical interest to synthetic biology and has practical applications in biomedicine. Fractals provide facili...

Identifying RNA 5-methylcytosine sites via pseudo nucleotide compositions.

Molecular bioSystems
RNA 5-methylcytosine (mC) plays an important role in numerous biological processes. Accurate identification of the mC site is helpful for a better understanding of its biological functions. However, the drawbacks of the experimental methods available...

MSLVP: prediction of multiple subcellular localization of viral proteins using a support vector machine.

Molecular bioSystems
Knowledge of the subcellular location (SCL) of viral proteins in the host cell is important for understanding their function in depth. Therefore, we have developed "MSLVP", a two-tier prediction algorithm for predicting multiple SCLs of viral protein...

A fuzzy logic controller based approach to model the switching mechanism of the mammalian central carbon metabolic pathway in normal and cancer cells.

Molecular bioSystems
Dynamics of large nonlinear complex systems, like metabolic networks, depend on several parameters. A metabolic pathway may switch to another pathway in accordance with the current state of parameters in both normal and cancer cells. Here, most of th...

Detecting reliable non interacting proteins (NIPs) significantly enhancing the computational prediction of protein-protein interactions using machine learning methods.

Molecular bioSystems
Protein-protein interactions (PPIs) play a vital role in most biological processes. Hence their comprehension can promote a better understanding of the mechanisms underlying living systems. However, besides the cost and the time limitation involved i...

Classifying pairs with trees for supervised biological network inference.

Molecular bioSystems
Networks are ubiquitous in biology, and computational approaches have been largely investigated for their inference. In particular, supervised machine learning methods can be used to complete a partially known network by integrating various measureme...

Predicting selective liver X receptor β agonists using multiple machine learning methods.

Molecular bioSystems
Liver X receptor (LXR) α and β are cholesterol sensors; they respond to excess cholesterol and stimulate reverse cholesterol transport. Activating LXRs represents a promising therapeutic option for dyslipidemia. However, activating LXRα may cause unw...