We propose a novel biologically constrained three-phase model of the brain microstructure. Designing a realistic model is tantamount to a packing problem, and for this reason, a number of techniques from the theory of ...

Background Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to identify patterns that together explain the ...

With the development of RDA and recommendations from the Working Group on the Future of Bibliographic Control, the presentation analyzes the future of cataloging standards and the recommendations from the Working Group.

Background Cancer/testis antigens (CTAs) were first discovered as immunogenic targets normally expressed in germline cells, but differentially expressed in a variety of human cancers. In this study, we used an integrative ...

Understanding the transport properties of a porous medium from a knowledge of its microstructure is a problem of great interest in the physical, chemical and biological sciences. Using a first passage time method, we compute ...

An in silico tool that can be utilized in the clinic to predict neoplastic progression and propose individualized treatment strategies is the holy grail of computational tumor modeling. Building such a tool requires the ...

Background Cell lines are used in experimental investigation of cancer but their capacity to represent tumor cells has yet to be quantified. The aim of the study was to identify significant alterations in pathway usage ...

In vitro selection of functional RNAs from large random sequence pools has led to the identification of many ligand-binding and catalytic RNAs. However, the structural diversity in random pools is not well understood. Such ...