The human genome project has had an impact on both biological research and its political organization; this review focuses primarily on the scientific novelty that has emerged from the project but also touches on its political dimensions. The project has generated both anticipated and novel information; in the later category are the description of the unusual distribution of genes, the prevalence of non-protein-coding genes, and the extraordinary evolutionary conservation of some regions of the genome. The applications of the sequence data are just starting to be felt in basic, rather than therapeutic, biomedical research and in the vibrant human origins and variation debates. The political impact of the project is in the unprecedented extent to which directed funding programs have emerged as drivers of basic research and the organization of the multidisciplinary groups that are needed to utilize the human DNA sequence.
[Show abstract][Hide abstract] ABSTRACT: Shotgun sequencing is the most powerful strategy for large scale sequencing. Two main approaches exist: clone-by-clone and whole genome shotgun (WGS). In the clone-by-clone strategy, overlapping clones are amplified and then sheared in a random fashion. In the WGS approach, a sufficient amount of cells from the target organism are obtained, and the random shearing is performed on extracted DNA. In both approaches, the resulting fragments are cloned and the fragment ends are subsequently sequenced, producing sequence reads. If a sufficient amount of sequence has been obtained, the reads will overlap in a way that makes it possible to deduce their correct order. A number of computer programs have been developed for this task. However, none of these programs are capable of producing correct assemblies if the target sequence contains repeats. This is because assembly algorithms in general are greedy, which means that when faced with different alternatives for the positioning of a read, the algorithm will fit the read at the first available position meeting the criteria for inclusion into the assembly. The resulting assemblies typically have the repeat regions degenerated, truncating the regions into a few copies with abnormally high shotgun coverage. This phenomenon occurs even when the repeat copies differ from each other, since the assembly programs are unable to distinguish the subtle differences between repeat elements from the sequencing errors produced by the sequencing apparatus . The work presented here is aimed at solving the repeat problem by detecting and utilizing single base differences between nearly identical repeats. In paper I, a statistical method for detecting repeat differences in the presence of sequencing errors was developed, implemented, and tested on simulated data. We showed that it is possible to obtain high specificity as well as sensitivity compared to other methods, by evaluating coinciding deviations from consensus in pairs of columns in multiple alignments. In paper II, a finishing tool (DNPTrapper) that visualizes the differences and enables manual and semi-automatic resolution of repeat regions was constructed and tested with simulated data as well as real data from the Trypanosoma cruzi WGS project. Results showed that using DNPTrapper, it is possible to resolve and analyze complicated repeat regions previously considered difficult or even impossible to resolve. Finally in paper III, five repeated genes in T. cruzi were analyzed using DNPTrapper. Different repeat characteristics in the parasite were described, and it was shown that thorough analysis of repeat regions is required for correcting erroneous consensus sequences of repeated genes in the assembly.
[Show abstract][Hide abstract] ABSTRACT: Background
Cancer remains one of the most complex diseases affecting humans and, despite the impressive advances that have been made in molecular and cell biology, how cancer cells progress through carcinogenesis and acquire their metastatic ability is still widely debated.
There is no doubt that human carcinogenesis is a dynamic process that depends on a large number of variables and is regulated at multiple spatial and temporal scales. Viewing cancer as a system that is dynamically complex in time and space will, however, probably reveal more about its underlying behavioural characteristics. It is encouraging that mathematicians, biologists and clinicians continue to contribute together towards a common quantitative understanding of cancer complexity. This way of thinking may further help to clarify concepts, interpret new and old experimental data, indicate alternative experiments and categorize the acquired knowledge on the basis of the similarities and/or shared behaviours of very different tumours.
Theoretical Biology and Medical Modelling 02/2006; 3(1):37. DOI:10.1186/1742-4682-3-37 · 0.95 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Genomic approaches to cancer are beginning to have an important impact in unraveling the complex etiologies of this disease, as well as allowing us to rationally treat afflicted patients. In this article, we will focus largely on genomic approaches to breast and prostate cancer susceptibility, as well as pharmacogenomic approaches to treatment. Current genomic approaches to cancer susceptibility have led to some significant, if not spectacular, successes which include breast cancer. More modest achievements, if not outright failures, such as in prostate cancer, are also notable and will be discussed further. We propose interdisciplinary approaches involving basic, clinical and population scientists to vigorously attack the cancer problem scientifically and with more organization. We highlight recent successes and suggest new approaches with a personal, if not provocative, perspective.
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