Download PDF by Nello Cristianini: Introduction to Computational Genomics: A Case Studies

By Nello Cristianini

ISBN-10: 0521856035

ISBN-13: 9780521856034

I've been searching for strong books on computational genomics or bioinformatics. besides the fact that, so much books that i've got encounted both think a organic heritage or is written in a slightly lengthy way.

This e-book is a smart creation for nonbiologist and is of average size (less than 2 hundred pages). A beginner could be in a position to examine the fundamentals from this e-book. each one bankruptcy offers a analyzing checklist, consisting of either traditionally very important references and references which are nonetheless of present interests.

The instances which are incorporated during this publication are really new and are nonetheless on the topic of examine frontiers during this box.

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Additional info for Introduction to Computational Genomics: A Case Studies Approach

Sample text

Each of them also has unique physical properties, but these will not be discussed until Chapter 4. 2 . 1 Sequence of an enzyme in H. influenzae. This is part of the amino acid sequence of the protein manganese-dependent superoxide dismutase in H. influenzae: HFDAQTMEIHHSKHHQAYVNNANAALEGLPAELVEMYPGHLISNLDKIPA EKRGALRNNAGGHTNHSLFWKSLKKGTTLQGALKDAIERDFGSVDAFKAE FEKAAATRFGSGWAWLVLTAEGKLAVVSTANQDNPLMGKEVAGCEGFPLL From genes to proteins. The simplest way to explain how proteins are made – ignoring many details and condensing complicated cellular reactions – is a simple diagram that shows what is known as the central dogma: DNA → RNA → Protein.

And: What is the threshold value of k such that 95% of random ORFs are shorter than k? This threshold will provide a lower bound on the length of ORFs to be kept by the algorithm given above. It is often the case in bioinformatics that such simple models can provide a first estimate of statistical significance. If we generate random sequences by a simple multinomial model, the answer can be calculated easily. Imagine a random process generating a sequence of DNA, and let us ask the probability of this process generating an ORF by chance.

Frequent words may be due to repetitive elements (a very common feature of certain genomes), gene regulatory features, or sequences with other biological functions. Rare motifs include binding sites for transcription factors (see Chapter 2), words such as CTAG that have undesirable structural properties (because they lead to “kinking” of the DNA), or words that are not compatible with the internal immune system of a bacterium. Bacterial cells can be infected by viruses, and in response they produce restriction enzymes, proteins that are capable of cutting DNA at specific nucleotide words, known as restriction sites.

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Introduction to Computational Genomics: A Case Studies Approach by Nello Cristianini


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