BE/BTech & ME/MTech Final Year Projects for Computer Science | Information Technology | ECE Engineer | IEEE Projects Topics, PHD Projects Reports, Ideas and Download | Sai Info Solution | Nashik |Pune |Mumbai
director@saiinfo settings_phone02536644344 settings_phone02048614848 settings_phone+919270574718 +919096813348 settings_phone+919028924212
logo


SAI INFO SOLUTION


Diploma | BE |B.Tech |ME | M.Tech |PHD

Project Development and Training

Search Project by Domainwise


An Improved Archaeology Algorithm based on Integrated Multi-source Biological Information for Yeast Protein Interaction Network


MICRO STRIP PATCH ANTENNA OPTI

AUTOMATIC RAIN STREAK REMOVAL:

Fault Node Recovery Algorithm
Abstract


With the development of high-throughput interaction detection techniques such as tandem affinity purification (TAP) and yeast two-hybrid (Y2H), the available genome-wide protein-protein interactions (PPIs) data have been increasing in recent years. Using mathematical, physical and artificial intelligence methods, some researchers in computational biology focused on uncovering the evolutionary ages of proteins according to present protein-protein interaction networks (PINs), but improving their accuracy waschallenging. A plausible explanation is that they solved biological problems by non-biological techniques and did not provide much attention to biological backgrounds and meanings of proteins or their relationships. In this article, we propose two ways to improve the accuracy of age predicting and skillfully ‚??embedding‚?? multi-source biological information in each iteration of an archaeology algorithm for yeast PIN. On the one hand, we reduce the probability of reversing errors by decreasing the non-duplication protein pairs, which are obtained from 460 gene trees constructed by means of a multiple sequence alignment (MSA) and the Neighbor Joining (NJ) algorithm. On the other hand, reliable crossover standard from different biological information sources can decrease local random errors of alternative treatment. The application of novel algorithm to simulation data and real yeast PPI networks shows a marked improvement in accuracy. Our research strongly suggests that putting non-biological methods into the ‚??biological context‚?? will bear more favourable results

KeyWords
PIN archaeology, algorithm, exclusion set, crossover standard, Kendall‚??s tau



Share
Share via WhatsApp
BE/BTech & ME/MTech Final Year Projects for Computer Science | Information Technology | ECE Engineer | IEEE Projects Topics, PHD Projects Reports, Ideas and Download | Sai Info Solution | Nashik |Pune |Mumbai
Call us : 09096813348 / 02536644344
Mail ID : developer.saiinfo@gmail.com
Skype ID : saiinfosolutionnashik