BioMed Research International / 2014 / Article / Tab 6

Research Article

A Knowledge-Driven Approach to Extract Disease-Related Biomarkers from the Literature

Table 6

Comparison of disease-biomarkers pairs identified by the text mining (TM) approach with disease-biomarkers annotations in DisGeNET, based on MeSH disease classification [31].

MeSH
disease class
MeSH disease class name Number of disease-biomarker associations The number validated with DisGeNET (%)

C01Bacterial infections and mycoses1,529164 (10.73)
C02Virus diseases3,297302 (9.16)
C03Parasitic diseases59082 (13.90)
C04Neoplasms31,6275,264 (16.64)
C05Musculoskeletal diseases5,771388 (6.72)
C06Digestive system diseases8,1541,156 (14.18)
C07Stomatognathic diseases 2,531195 (7.70)
C08Respiratory tract diseases5,460735 (13.46)
C09Otorhinolaryngologic diseases 77040 (5.19)
C10Nervous system diseases10,8191,132 (10.46)
C11Eye diseases2,513226 (8.99)
C12Male urogenital diseases5,110666 (13.03)
C13Female urogenital diseases and pregnancy complications6,432863 (13.42)
C14Cardiovascular diseases9,3101,393 (14.96)
C15Hemic and lymphatic diseases7,689948 (12.33)
C16Congenital, hereditary, and neonatal diseases and abnormalities10,382397 (3.82)
C17Skin and connective tissue diseases6,724851 (12.66)
C18Nutritional and metabolic diseases 6,314711 (11.26)
C19Endocrine system diseases5,253681 (12.96)
C20Immune system diseases 10,2101,393 (13.64)
C21Disorders of environmental origin20 (0.00)
C23Pathological conditions, signs, and symptoms 8,212606 (7.38)
C24Occupational diseases 7211 (15.28)
F01Behavior and behavior mechanisms59424 (4.04)
F03Mental disorders2,810613 (21.89)