1 - 7 of 7 results

OCDD / Obesity and Co-morbid Disease Database

Allows exploration of molecular connections of obesity and its comorbid diseases. OCDD was built by applying a computational pipeline that performs both text mining on literature databases and biological network mining on systems biology databases. This database is useful to understand the complexity of developing comorbid diseases in molecular level. It provides functional annotation of common genes, gene interaction networks and key driver analyses.

TMPM-ICD9 / Trauma Mortality Prediction Model based on ICD9

Provides a ICD-9 injury model. TMPM-ICD9 is a probit regression model which includes the model-averaged regression coefficients (MARC) values for the 5 most severe injuries sustained by a patient as predictor variables. This model represents a significant improvement in existing injury scoring systems based on administrative data. It is based on universally available ICD-9-CM codes and could be used by virtually any hospital caring for trauma patients.


An interactive plugin for Cytoscape that can be used to search, explore, analyse and visualise human Disease Comorbidity Network (DCN). CytoCom represents disease-disease associations in terms of bipartite graphs and provides ICD9 (International Classification of Diseases, Ninth Revision)-centric and disease name centric views of disease information. It allows users to find associations between diseases based on the two measures: Relative Risk (RR) and varphi-correlation values. In the disease network, the size of each node is based on the prevalence of that disease. CytoCom is capable of clustering disease network based on the ICD9 disease category. It provides user-friendly access that facilitates exploration of human diseases, and finds additional associated diseases by double-clicking a node in the existing network. Additional comorbid diseases are then connected to the existing network. It is able to assist users for interpretation and exploration of the human diseases by a variety of built-in functions. Moreover, CytoCom permits multi-coloring of disease nodes according to standard disease classification for expedient visualisation.


An R software to compute novel estimators of the disease comorbidity associations. Starting from an initial diagnosis, genetic and clinical data of a patient comoR identifies the risk of disease comorbidity. Then it provides a pipeline with different causal inference packages (e.g. pcalg, qtlnet etc) to predict the causal relationship of diseases. It also provides a pipeline with network regression and survival analysis tools (e.g. Net-Cox, rbsurv etc) to predict more accurate survival probability of patients. The input of this software is the initial diagnosis for a patient and the output provides evidences of disease comorbidity mapping.