title: Recent progress in predicting protein sub-subcellular locations.
abstract: In the last two decades, the number of the known protein sequences increased very rapidly. However, a knowledge of protein function only exists for a small portion of these sequences. Since the experimental approaches for determining protein functions are costly and time consuming, in silico methods have been introduced to bridge the gap between knowledge of protein sequences and their functions. Knowing the subcellular location of a protein is considered to be a critical step in understanding its biological functions. Many efforts have been undertaken to predict the protein subcellular locations in silico. With the accumulation of available data, the substructures of some subcellular organelles, such as the cell nucleus, mitochondria and chloroplasts, have been taken into consideration by several studies in recent years. These studies create a new research topic, namely 'protein sub-subcellular location prediction', which goes one level deeper than classic protein subcellular location prediction.
authors.affiliation: School of Computer Science and Technology, Tianjin University, Tianjin 300072, China.
authors.forename: Pufeng
authors.initials: P
authors.lastname: Du
authors.forename: Tingting
authors.initials: T
authors.lastname: Li
authors.forename: Xin
authors.initials: X
authors.lastname: Wang
mesh_terms: D000818:Animals; D006801:Humans; D008962:Models, Theoretical; D011506:Proteins / Q000378:metabolism*
chemical_list: D011506:Proteins