From ‘omes to biology

Abstract

SummaryTechnologies that have emerged from the genome project have dramatically increased our ability to generate data on the way in which organisms respond to their environments, how they execute their programmes of development and growth, and how these are altered in the development of disease states. However, our ability to analyse these large datasets has not kept pace with our ability to generate them and consequently new strategies must be developed to address the issues associated with their analysis. One approach that we have employed quite successfully is to look at data from microarrays (or proteomics or metabolomics experiments) not as independent datasets, but rather as elements of a much larger body of biological information across various scales that must be integrated with, and interpreted within, the context of such ancillary data. Here we outline the general approach and provide three examples from published studies of the way in which we have applied this strategy.

Integration of structural and functional genomics

“…Dr Quackenbush presented a global view on mining large transcriptional profiling data sets that are currently available in a number of species (Quackenbush 2006). He is a recognized leader in the production and analysis of global gene expression data (Quackenbush 2002).…”

New Challenges for Old Diseases: The Impact of -Omics Technologies in the Understanding of Allergic Diseases

“…Two major types of arrays have been developed: oligonucleotide (use short oligonucleotides synthesised on the array matrix) and cDNA arrays (employs probes of copy-DNA). There are two basic approaches to generate microarray data ( Quackenbush, 2006). In a twocolor array, two samples of RNA, each labelled with a different dye, are simultaneously hybridized to the array.…”

“…The technology that the genome project has enabled, rather than the data it has produced, has induced the most profound impact on our conduct of biological research. In particular, functional genomics approaches, suchs as DNA microarrays, proteomics and metabolomics have greatly increased the rate at which we can generate data on biological systems allowing us, to begin to observe on a molecular level the holistic response of an organism to a particular stimulus (Quackenbush, 2006). In this review, will be summarize the principle of these new methodologies and the impact of omics-techniques, mainly genomic-transcriptomics (analysis of single nucleotide polymorphisms or gene-expression) and proteomic (identification and quantification of proteins), in the knowledge of different aspects of allergy diseases (diagnosis, screening, monitoring of treatment, protective or risk biomarkers and drug development) and the advance to define the personalized and molecular medicine in this complex kind of diseases.…”

Bioinformatics applied to gene transcription regulation

“…Completion of the human genome reference and development of next-generation sequencing (NGS) has led to an exciting era in which the complexity of biomedical research can be tackled in a new way, requiring multidisciplinary expertise at multiple levels (Noble 2002, Quackenbush 2006b, Navlakha & Bar-Joseph 2011. Bioinformatics, as an integrative discipline in this field, increasingly occupies a larger portion of the biomedical stage.…”

“…However, most efforts cannot yet fully rely on such coherent supporting frameworks. Instead, expertise and knowledge of heterogeneous tools are required (Bialek & Botstein 2004, Pevzner 2004, Wasserman & Sandelin 2004, Quackenbush 2006b, Wingreen & Botstein 2006, Dudley & Butte 2009, Pevzner & Shamir 2009). Here, I want to collect a few reference landmarks for technology professionals who want to enter the postgenomic biology era and for biomedical investigators and students who want to build bioinformatics expertise on their own.…”