SE-BLTCNN: A channel attention adapted deep learning model based on PSSM for membrane protein classification

Predicting protein subcellular location with network embedding and enrichment features

(2020) Xiaoyong Pan et al.   BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS

Efficient utilization on PSSM combining with recurrent neural network for membrane protein types prediction

(2019) Shunfang Wang et al.   COMPUTATIONAL BIOLOGY AND CHEMISTRY

Squeeze-and-Excitation Networks

(2019) Jie Hu et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Prediction of human protein subcellular localization using deep learning

(2018) Leyi Wei et al.   JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING

Predicting membrane protein types by incorporating protein topology, domains, signal peptides, and physicochemical properties into the general form of Chou’s pseudo amino acid composition

(2012) Yen-Kuang Chen et al.   JOURNAL OF THEORETICAL BIOLOGY

Pseudo Amino Acid Composition and its Applications in Bioinformatics, Proteomics and System Biology

(2009) Kuo-Chen Chou   Current Proteomics

An ensemble of support vector machines for predicting the membrane protein type directly from the amino acid sequence

(2008) Loris Nanni et al.   AMINO ACIDS

Predicting Membrane Protein Types by the LLDA Algorithm

(2008) Tong Wang et al.   PROTEIN AND PEPTIDE LETTERS