Modern molecular methods in biology and medicine are producing an unprecedented amount of data which are withstanding manual analysis by their mere volume.
Computerized methods have so far mainly been developed for sequence data, while data from
- DNA chips
- DNA Microarrays represent an important step towards the comprehensibility of organisms on the genomic level. Transcriptional activities of tens of thousands of genes can be determined at the same time, even the whole genome of one organism can be investigated. This process provides huge quantities of data, which can only be investigated by computerized methods.
- Proteomic analyses by 2D gel electrophoresis or mass spectrometry
- Comparative genomic hybridization (CGH)
- Multicolor fluorescent in-situ hybridization (FISH)
- Loss-of-heterozygosity analysis (LOH)
- Single nucleotide polymorphism (SNP) analysis
still present a major challenge to computational biology to find associations between such molecular data and clinical information like tumor stage or grade, disease progression, degree of malignancy or responsiveness to chemotherapy.
In a systems biology approach experimental studies of signal networks are enriched by quantitative modelling and simulation of cellular processes.
Although spatial distribution of signals plays an essential role for their processing, our knowledge in this field is very limited. Image processing tools to quantitatively evaluate microscopical data and mathematical modelling will help us to elucidate the spatio-temporal dynamics of signal transduction networks. Spatial modelling as a systems biology approach can help to understand how signalling pathways are regulated through barriers like membranes and throughout different compartments or cells.
With the upcoming flood of different biological data, modelling and simulation techniques will play a key role in the understanding of cellular systems and their interactions.
As opposed to using computers and all the currently available software techniques as tools in the fight against cancer, Biomatics on the other hand offers techniques to study Cancer as a fundamentally computational process in and of itself. In other words the similarity of the biological world to man made computers is examined in the hopes of using those principles to discover the underlying mechanisms of the disease process. If in fact some aspects of Cancer are computational in nature then input from computer scientists is indispensable.
At least some forms of Cancer are now accepted to be as a result of epigenetic factors. Understanding
The Amino Acid Code
The Histone Code
are some examples where principles of computation are central in this pursuit.
SigPath is an information system designed to support quantitative studies on the signaling pathways and networks of the cell.
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The researchers found that podocalyxin significantly expands the non-adhesive face of cells, allowing individual cells to brush aside adhesion molecules situated between tumour cells.
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