Computational Biology Research Paper

Computational Biology Research Paper-38
Our tools have led to the discovery and characterization of many of the known classes of bacterial riboswitches, and point to the presence of thousands of novel nc RNAs in the human genome. Identifying the Genetic Basis of Complex Traits (Lee) Humans differ in many observable qualities, termed "phenotypes", ranging from appearance to disease susceptibility.Many phenotypes are largely determined by each individual's specific "genotype", stored in the 3.2 billion bases (A, C, G, and T) of his or her DNA sequence.Professors Lee, Ruzzo, Seelig, and Tompa, together with their students, collaborate with molecular biologists on a wide range of computational problems related to the analysis of biological sequences.

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If we can decipher the sequence by identifying which sequence variations affect a certain phenotype, it would make a great impact on human life.

In recent years, it has become possible to retrieve an individual's sequence information on a genome-wide scale.

Programmed molecular self-assembly will be used for the massively parallel construction of nanoscale devices.

"Smart drugs" that target drug activity to disease cells and activate in response to specific molecular clues will have minimal side effects and improve therapeutic outcomes.

However, classical approaches focusing on genotype-phenotype correlation often fail in identifying significant associations between genotype and phenotype.

Variation in the DNA sequence can perturb a complex web of interactions among a number of biological molecules, and that change of the system can lead to phenotypic variation.Motifs in Nucleotide and Protein Sequences (Tompa) Once sequencing is completed, how does one discover which portions of the genome are functional, and what their functions are?Computational tools can be extremely useful for pruning the search space of experiments, efficiently suggesting potentially functional regions on which to focus our limited laboratory resources.A natural application of this idea arises in the study of gene regulation.One of the challenges currently facing biologists is to understand the varied and complex mechanisms that regulate how, when, where, and at what rate genes express their products.This approach has been called phylogenetic footprinting.The simple premise underlying phylogenetic footprinting is that selective pressure causes functional elements to evolve at a slower rate than nonfunctional sequences.Computational Molecular Biology Overview Molecular Biology has become an information science with close ties to Computer Science.Large databases and sophisticated algorithms have become essential tools for biologists seeking to understand complex biological systems, determine the functions of nucleotide and protein sequences, or reconstruct the course of evolution.We have developed algorithms that search for statistically overrepresented motifs in such a collection of regulatory regions, these motifs being good candidate binding sites.An orthogonal approach deduces binding sites by considering orthologous regulatory regions of a single gene from multiple species.

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