KEGG: a database resource of biological system [11].
Whenever a shared database resource, containing critical patient data, is created, protecting the contents of the database is a high priority goal.
The Lung Image Database Consortium LIDCC) and Image Database Resource Initiative (IDRI) is the largest publicly available computed tomography (CT) image reference data set of lung nodules.
Different from database resource, the Web document set cannot be normalized in order to keep the data consistency and storage minimization.
Clean, structured and high quality data stored in a relational database resource can facilitate computational predictive modeling, thus allowing for new information to be inferred by computational analyses.
The present study describes our preliminary work to build a new database resource from the PubChem3D project, namely, PubChem structure activity relationship (SAR) clusters [29].
Data from the different databases are publicly available, and collected useful for data analytics as follows: KEGG: a database resource of biological system [11].
The method has been validated using the first dataset of studies acquired and described by the Lung Image Database Consortium LIDCC) and by its latest release – the LIDC IDRI (Image Database Resource Initiative) database.
KEGG (http://www.genome.jp/kegg/) is a database resource for understanding functions and utilities of the biological system from molecular-level information, especially large-scale molecular datasets generated by genome sequencing.
To the best of our knowledge, a database resource that provides such a set of information and features does not yet exist.
Although no genotype-related abnormality is reported in lungs of adult mutant mice in the international database resource for the laboratory mouse (http://www.informatics.jax.org/external/ko/deltagen/1241.html), lung development was not extensively studied in these mice.
