This paper examines recent developments and applications of Hidden Markov Models (HMMs) to various problems in computational biology, including multiple sequence alignment, homology detection, protein sequences classification, and genomic annotation.
Computational Biology ; Markov Chains ; Models, Biological ; Protein Conformation ; Sequence Alignment ; Sequence Homology

OBJECTIVETo investigate the effect of smoking on the microRNAs (miRNAs) expression in pneumoconiosis patients.

METHODSReal-time qPCR was used to measure the expression levels of miR-21, miR-200c, miR-16, miR-204, miR-206, miR-155, let-7g, miR-30b, and miR-192 in 36 non-smoking patients with pneumoconiosis and 38 smoking patients with pneumoconiosis, and the differences in expression levels between the two groups were evaluated by two-independent samples t-test.

RESULTSThe expression of miR-192 in serum showed a significant difference between non-smoking and smoking pneumoconiosis patients (P < 0.05), and it decreased gradually in smoking patients with stage I and II pneumoconiosis. In the serum of all pneumoconiosis patients, the expression level of miR-16 was the highest, while the expression level of miR-204 was the lowest.

CONCLUSIONPneumoconiosis patients have differential expression of miRNAs in serum, and smoking has an effect on the miRNAs expression in pneumoconiosis patients.

Humans ; MicroRNAs ; biosynthesis ; Pneumoconiosis ; metabolism ; physiopathology ; Polymerase Chain Reaction ; Smoking ; adverse effects