2 research outputs found
Hematopoietic Cell Types: Prototype for a Revised Cell Ontology
The Cell Ontology (CL) is an OBO Foundry candidate ontology intended for the representation of cell types from all of biology. A recent workshop sponsored by NIAID on hematopoietic cell types in the CL addressed issues of both the content and structure of the CL. The section of the ontology dealing with hematopoietic cells was extensively revised, and plans were made for restructuring these cell type terms as cross-products with logical definitions based on relationships to external ontologies, such as the Protein Ontology and the Gene Ontology. The improvements to the CL in this area represent a paradigm for the future revision of the whole of the CL
Next-generation information systems for genomics
NIH Grant no. HG00739The advent of next-generation sequencing technologies is transforming
biology by enabling individual researchers to sequence the
genomes of individual organisms or cells on a massive scale. In order
to realize the translational potential of this technology we will need
advanced information systems to integrate and interpret this deluge
of data. These systems must be capable of extracting the location and
function of genes and biological features from genomic data, requiring
the coordinated parallel execution of multiple bioinformatics analyses
and intelligent synthesis of the results. The resulting databases must
be structured to allow complex biological knowledge to be recorded
in a computable way, which requires the development of logic-based
knowledge structures called ontologies. To visualise and manipulate
the results, new graphical interfaces and knowledge acquisition tools
are required. Finally, to help understand complex disease processes,
these information systems must be equipped with the capability to
integrate and make inferences over multiple data sets derived from
numerous sources.
RESULTS:
Here I describe research, design and implementation of some of
the components of such a next-generation information system. I first
describe the automated pipeline system used for the annotation of
the Drosophila genome, and the application of this system in genomic
research. This was succeeded by the development of a flexible graphoriented
database system called Chado, which relies on the use of
ontologies for structuring data and knowledge. I also describe research
to develop, restructure and enhance a number of biological
ontologies, adding a layer of logical semantics that increases the computability
of these key knowledge sources. The resulting database and
ontology collection can be accessed through a suite of tools. Finally
I describe how the combination of genome analysis, ontology-based
database representation and powerful tools can be combined in order
to make inferences about genotype-phenotype relationships within and
across species.
CONCLUSION:
The large volumes of complex data generated by high-throughput
genomic and systems biology technology threatens to overwhelm us,
unless we can devise better computing tools to assist us with its analysis.
Ontologies are key technologies, but many existing ontologies are
not interoperable or lack features that make them computable. Here
I have shown how concerted ontology, tool and database development
can be applied to make inferences of value to translational research