This will include not just Bayes' theorem but a range of information pertaining to the collection and characterization of the data, including information about how to sample the world, how and what to store, what conditions to consider reliable, relations between samples and populations, etc.
This chapter emphasizes the importance of development of appropriate computational approaches to working with biological data to provide an understanding and characterization of those data.
Multivariate techniques have been used for evaluation and characterization of analytical data (Fadigas et al. [2010]).
This representation is called the ONMF mutation profile (ONMF-MP); it is used for efficient search and characterization of patients' genome data, and provides basic information for many data mining tasks in translational bioinformatics.
The presented work shows that a Multivariate Gaussian Mixture Model as a framework for data-integration is suitable for the analysis and characterization of synthetic lethality data.
Furthermore, taking advantage of the ISAconverter, the experience of mapping into an existing schema, such SRA xml schema, proved to be of great help in informing the definition of classes under the Basic Formal Ontology (BFO) framework and facilitated the processing and characterization of the NEON data collection template (Fig. 1).
The current study was based on the population-based data from the Taiwan cancer registry (TCR) and aimed to broaden the availability and comparability of data and characterization of BC incidence in all age groups.
In this paper, we outline an approach that defines visualizations operations or basic visual actions that implement a viewer's task of exploration and characterization of geospatial structures in data or phenomena.
Although several high throughput technologies have been developed for rapid sequencing and characterization of transcriptomes, expressed sequence data are still not available for many organisms, including crop plants.
In this paper we describe the development of a collection of 3′-cDNA 454 reads derived from multiple Lens species and genotypes, the identification and characterization of SNPs from this data, the selection of a subset of SNPs for the development of a 1,536 SNP Illumina GoldenGate array and the use of the array to generate a comprehensive linkage map for a L. culinaris genetic mapping population.
