RESUMEN
AIM: To analyze the metastasis-related proteins in hepatocellular carcinoma (HCC) and discover the biomarker candidates for diagnosis and therapeutic intervention of HCC metastasis with bioinformatics tools. METHODS: Metastasis-related proteins were determined by stable isotope labeling and MS analysis and analyzed with bioinformatics resources, including Phobius, Kyoto encyclopedia of genes and genomes (KEGG), online mendelian inheritance in man (OMIM) and human protein reference database (HPRD). RESULTS: All the metastasis-related proteins were linked to 83 pathways in KEGG, including MAPK and p53 signal pathways. Protein-protein interaction network showed that all the metastasis-related proteins were categorized into 19 function groups, including cell cycle, apoptosis and signal transduction. OMIM analysis linked these proteins to 186 OMIM entries. CONCLUSION: Metastasis-related proteins provide HCC cells with biological advantages in cell proliferation, migration and angiogenesis, and facilitate metastasis of HCC cells. The bird's eye view can reveal a global characteristic of metastasis-related proteins and many differentially expressed proteins can be identified as candidates for diagnosis and treatment of HCC.
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Biomarcadores de Tumor/análisis , Carcinoma Hepatocelular/química , Biología Computacional , Neoplasias Hepáticas/química , Proteínas de Neoplasias/análisis , Carcinoma Hepatocelular/patología , Línea Celular Tumoral , Bases de Datos Genéticas , Humanos , Neoplasias Hepáticas/patología , Metástasis de la Neoplasia , Pronóstico , Mapeo de Interacción de Proteínas , Proteómica , Espectrometría de Masa por Láser de Matriz Asistida de Ionización Desorción , Espectrometría de Masas en TándemRESUMEN
A new method for predicting the gene acceptor site based on multi-objective optimization is introduced in this paper. The models for the acceptor, branch and distance between acceptor site and branch site were constructed according to the characteristics of the sequences from the exon-intron database and using common biological knowledge. The acceptor function, branch function and distance function were defined respectively, and the multi-objective optimization model was constructed to recognize the splice site. The test results show that the algorithm used in this study performs better than the SplicePredictor, which is one of the leading acceptor site detectors.
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Exones , Intrones , Sitios de Empalme de ARN/genética , Empalme del ARN/fisiología , Algoritmos , Biología Computacional , Modelos Genéticos , Análisis de SecuenciaRESUMEN
In the present paper, we describe how a directed graph was constructed and then searched for the optimum path using a dynamic programming approach, based on the secondary structure propensity of the protein short sequence derived from a training data set. The protein secondary structure was thus predicted in this way. The average three-state accuracy of the algorithm used was 76.70%.