Background:
Essential proteins play important roles in the survival or reproduction of
an organism and support the stability of the system. Essential proteins are the minimum set of
proteins absolutely required to maintain a living cell. The identification of essential proteins is a
very important topic not only for a better comprehension of the minimal requirements for cellular
life, but also for a more efficient discovery of the human disease genes and drug targets.
Traditionally, as the experimental identification of essential proteins is complex, it usually requires
great time and expense. With the cumulation of high-throughput experimental data, many
computational methods that make useful complements to experimental methods have been
proposed to identify essential proteins. In addition, the ability to rapidly and precisely identify
essential proteins is of great significance for discovering disease genes and drug design, and has
great potential for applications in basic and synthetic biology research.
Objective:
The aim of this paper is to provide a review on the identification of essential proteins
and genes focusing on the current developments of different types of computational methods, point
out some progress and limitations of existing methods, and the challenges and directions for
further research are discussed.
T-16 Modeling and Experimental Identification for Muscular Force Estimation Based on Evoked EMG in FES
