Biomedical subjects

Man-Ling Lee

Publications and source records attributed to Man-Ling Lee.

3 recordsLinked to original sources

PubMedDate not supplied

DISE: directed sphere exclusion.

The Sphere Exclusion algorithm is a well-known algorithm used to select diverse subsets from chemical-compound libraries or collections. It can be applied with any given distance measure between two structures. It is popular because of the intuitive geometrical interpretation of the method and its good performance on large data sets. This paper describes Directed Sphere Exclusion (DISE), a modification of the Sphere Exclusion algorithm, which retains all positive properties of the Sphere Exclusion algorithm but generates a more even distribution of the selected compounds in the chemical space. In addition, the computational requirement is significantly reduced, thus it can be applied to very large data sets.

Algorithms↗

PubMedDate not supplied

Process-driven information management system at a biotech company: concept and implementation.

While established pharmaceutical companies have chemical information systems in place to manage their compounds and the associated data, new startup companies need to implement these systems from scratch. Decisions made early in the design phase usually have long lasting effects on the expandability, maintenance effort, and costs associated with the information management system. Careful analysis of work and data flows, both inter- and intradepartmental, and identification of existing dependencies between activities are important. This knowledge is required to implement an information management system, which enables the research community to work efficiently by avoiding redundant registration and processing of data and by timely provision of the data whenever needed. This paper first presents the workflows existing at Anadys, then ARISE, the research information management system developed in-house at Anadys. ARISE was designed to support the preclinical drug discovery process and covers compound registration, analytical quality control, inventory management, high-throughput screening, lower throughput screening, and data reporting.

Journal Article↗

PubMedDate not supplied

A searching and reporting system for relational databases using a graph-based metadata representation.

Relational databases are the current standard for storing and retrieving data in the pharmaceutical and biotech industries. However, retrieving data from a relational database requires specialized knowledge of the database schema and of the SQL query language. At Anadys, we have developed an easy-to-use system for searching and reporting data in a relational database to support our drug discovery project teams. This system is fast and flexible and allows users to access all data without having to write SQL queries. This paper presents the hierarchical, graph-based metadata representation and SQL-construction methods that, together, are the basis of this system's capabilities.

Computer Simulation↗