Using pseudo amino acid composition to predict transmembrane regions in protein: cellular automata and Lempel-Ziv complexity

Transmembrane (TM) proteins represent about 20-30% of the protein sequences in higher eukaryotes, playing important roles across a range of cellular functions. Moreover, knowledge about topology of these proteins often provides crucial hints toward their function. Due to the difficulties in experime...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Amino acids Ročník 34; číslo 1; s. 111 - 117
Hlavní autori:	Diao, Y, Ma, D, Wen, Z, Yin, J, Xiang, J, Li, M
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Vienna Vienna : Springer-Verlag 2008 Springer-Verlag Springer Nature B.V
Predmet:	Amino acid composition Amino acid sequence amino acid sequences Amino acids Amino Acids - chemistry Amino Acids - metabolism Analytical Chemistry Augmented covariant-discriminant algorithm Automata theory Biochemical Engineering Biochemistry Biomedical and Life Sciences Cellular automata Cellular structure Chou's invariance theorem Complexity Composition Computational Biology data collection drugs Eukaryotes eukaryotic cells Genetics Lempel-Ziv complexity Life Sciences Mathematical models Membrane proteins Membrane Proteins - chemistry Membrane Proteins - metabolism Membranes Models, Molecular Neurobiology prediction Protein structure Protein Structure, Secondary Protein Structure, Tertiary Proteins Proteomics Pseudo amino acid composition Sequence Analysis, Protein Source code Structure-function relationships Topology Transmembrane regions Keywords: Cellular automata – Pseudo amino acid composition – Lempel-Ziv complexity – Augmented covariant-discriminant algorithm – Chou’s invariance theorem – Transmembrane regions
ISSN:	0939-4451, 1438-2199, 1438-2199
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!