📘 ❞ Algorithms in computational biology-Aarhus ❝ كتاب ــ كاتب غير معروف اصدار 2000

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█ _ كاتب غير معروف 2000 حصريا كتاب ❞ Algorithms in computational biology Aarhus ❝ 2024 Aarhus: نبذه عن الكتاب: In this thesis we are concerned with constructing algorithms that address problems of biological relevance This activity is part a broader interdisciplinary area called biology, or bioinformatics, focuses on utilizing the capacities computers to gain knowledge from data The majority relate molecular evolutionary and focus analyzing comparing genetic material of organisms One deciding factor shaping area biology is DNA, RNA proteins responsible for storing utilizing the an organism, can be described as strings over finite alphabets The string representation biomolecules allows wide range of algorithmic techniques applied and comparing We contribute field biology by to biological sequence analysis structure prediction The organisms evolves by discrete mutations, most prominently substitutions, insertions deletions nucleotides Since genetic material stored DNA sequences reflected protein sequences, it makes sense compare two more look for similarities differences used infer relatedness the sequences In consider problem sequences of coding when relationship between taken into account do using model penalizes event by the change induces encoded analyze detail, construct alignment algorithm improves existing best alignment reducing its running time quadratic factor our equal the running based much simpler models Biology Books مجاناً PDF اونلاين Biologically Biology natural science study life, various forms function, how these interact each other surrounding environment word Greek made up words: bio (βίος) meaning life And loggia ( λογία) means Biology: similarity vegetation animal cover edges African American states, existence same fossil Branches biology Biology ancient thousands years old modern began nineteenth century has multiple branches Among them are: Anatomy Botany Biochemia Biogeography Biofisia Cytology cell science Ecology environmental science Development Embryology embryology Genetics genetics Histology histology Anthropology anthropology Microbiology bacteriology Molecular Biology Physiology functions organs Taxonemia taxonomy Virology virology Zoology zoology

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Algorithms in computational biology-Aarhus
كتاب

Algorithms in computational biology-Aarhus

ــ كاتب غير معروف

صدر 2000م
Algorithms in computational biology-Aarhus
كتاب

Algorithms in computational biology-Aarhus

ــ كاتب غير معروف

صدر 2000م
عن كتاب Algorithms in computational biology-Aarhus:
نبذه عن الكتاب:

In this thesis we are concerned with constructing algorithms that address problems of biological relevance. This activity is part of a broader interdisciplinary
area called computational biology, or bioinformatics, that focuses on utilizing the capacities of computers to gain knowledge from biological data. The
majority of problems in computational biology relate to molecular or evolutionary biology, and focus on analyzing and comparing the genetic material of
organisms. One deciding factor in shaping the area of computational biology
is that DNA, RNA and proteins that are responsible for storing and utilizing
the genetic material in an organism, can be described as strings over finite alphabets. The string representation of biomolecules allows for a wide range of
algorithmic techniques concerned with strings to be applied for analyzing and
comparing biological data. We contribute to the field of computational biology
by constructing and analyzing algorithms that address problems of relevance to
biological sequence analysis and structure prediction.
The genetic material of organisms evolves by discrete mutations, most prominently substitutions, insertions and deletions of nucleotides. Since the genetic
material is stored in DNA sequences and reflected in RNA and protein sequences, it makes sense to compare two or more biological sequences to look
for similarities and differences that can be used to infer the relatedness of the
sequences. In the thesis we consider the problem of comparing two sequences
of coding DNA when the relationship between DNA and proteins is taken into
account. We do this by using a model that penalizes an event on the DNA by
the change it induces on the encoded protein. We analyze the model in detail, and construct an alignment algorithm that improves on the existing best
alignment algorithm in the model by reducing its running time by a quadratic
factor. This makes the running time of our alignment algorithm equal to the
running time of alignment algorithms based on much simpler models.
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