Books > Science & Mathematics > Biology, life sciences > Cellular biology
|
Buy Now
Computational Prediction of Protein Complexes from Protein Interaction Networks (Paperback)
Loot Price: R2,082
Discovery Miles 20 820
|
|
Computational Prediction of Protein Complexes from Protein Interaction Networks (Paperback)
Series: ACM Books
Expected to ship within 10 - 15 working days
|
Complexes of physically interacting proteins constitute fundamental
functional units that drive almost all biological processes within
cells. A faithful reconstruction of the entire set of protein
complexes (the "complexosome") is therefore important not only to
understand the composition of complexes but also the higher level
functional organization within cells. Advances over the last
several years, particularly through the use of high-throughput
proteomics techniques, have made it possible to map substantial
fractions of protein interactions (the "interactomes") from model
organisms including Arabidopsis thaliana (a flowering plant),
Caenorhabditis elegans (a nematode), Drosophila melanogaster (fruit
fly), and Saccharomyces cerevisiae (budding yeast). These
interaction datasets have enabled systematic inquiry into the
identification and study of protein complexes from organisms.
Computational methods have played a significant role in this
context, by contributing accurate, efficient, and exhaustive ways
to analyze the enormous amounts of data. These methods have helped
to compensate for some of the limitations in experimental datasets
including the presence of biological and technical noise and the
relative paucity of credible interactions. In this book, we
systematically walk through computational methods devised to date
(approximately between 2000 and 2016) for identifying protein
complexes from the network of protein interactions (the
protein-protein interaction (PPI) network). We present a detailed
taxonomy of these methods, and comprehensively evaluate them for
protein complex identification across a variety of scenarios
including the absence of many true interactions and the presence of
false-positive interactions (noise) in PPI networks. Based on this
evaluation, we highlight challenges faced by the methods, for
instance in identifying sparse, sub-, or small complexes and in
discerning overlapping complexes, and reveal how a combination of
strategies is necessary to accurately reconstruct the entire
complexosome.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
|
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.