Classification of lung cancer tumors based on structural and physicochemical properties of proteins by bioinformatics models

PLoS ONE

Volumn 7, Issue 7, 2012, Pages

  Hosseinzadeh, Faezeh ^a   Ebrahimi, Mansour ^b   Goliaei, Bahram ^c   Shamabadi, Narges ^b  

^a UNIVERSITY OF TEHRAN   (Iran)

^b UNIVERSITY OF QOM   (Iran)

^c IRAN UNIVERSITY OF MEDICAL SCIENCES   (Iran)

Author keywords

[No Author keywords available]

Indexed keywords

CYSTEINE; DIPEPTIDE; GLUTAMIC ACID; GLYCINE; METHIONINE; PHENYLALANINE; THREONINE; VALINE;

AMINO ACID SEQUENCE; ARTICLE; ATTRIBUTE WEIGHTING ALGORITHM; BIOINFORMATICS; CANCER CLASSIFICATION; CLASSIFICATION ALGORITHM; DATA MINING; DECISION STUMP INDUCTION MODEL; DECISION TREE INDUCTION MODEL; DECISION TREE PARALLEL INDUCTION MODEL; DIAGNOSTIC ACCURACY; GENE SEQUENCE; HUMAN; HYDROPHOBICITY; LUNG NON SMALL CELL CANCER; LUNG SMALL CELL CANCER; LUNG TUMOR; MAJOR CLINICAL STUDY; MICROARRAY ANALYSIS; PHYSICAL CHEMISTRY; PREDICTION; PROTEIN ANALYSIS; PROTEIN STRUCTURE; RANDOM FOREST INDUCTION MODEL; RANDOM TREE INDUCTION MODEL; SPATIAL AUTOCORRELATION ANALYSIS; SUPERVISED CLUSTERING ALGORITHM; UNSUPERVISED CLUSTERING ALGORITHM;

COMPUTATIONAL BIOLOGY; DATA MINING; HUMANS; LUNG NEOPLASMS; PROTEINS;

EID: 84864070170     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0040017     Document Type: Article

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