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Analysis and fast prediction of lnrRNA transcripts using weighted K-mers adjacency (WeKA) Kernels / Talha Irfan.

By: Irfan, TalhaContributor(s): Sup: Dr. Arslan Shaukat Material type: Text

TextPublisher: Islamabad: CEME - NUST, 2016Description: 48 p.: ill.; 30cmSubject(s): Computer Engineering - MS ThesesDDC classification: 621.39

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Item type	Current location	Home library	Shelving location	Call number	Status	Date due	Barcode	Item holds
Thesis	Central Library (CL)	Central Library (CL)	Thesis	621.39 (Browse shelf)	Available		CL-T-796

Total holds: 0

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Previous	621.39 KLT based predictive aircraft tracking in low resolution images /	621.39 Malware detection using static and dynamic features of a portable excutable (PE) file /	621.39 A DISTRIBUTED ARITHMETIC BASED IMPLEMENTATION OF ADAPTIVE FILTER AND DESIGN ANALYSIS	621.39 Analysis and fast prediction of lnrRNA transcripts using weighted K-mers adjacency (WeKA) Kernels /	621.39 MFCC and Spectro- Temporal Gabor Filter bank Features for Acoustic Event Detection /	621.39 To develop genetic algorithm and optimized heuristic algorithm based smart nano-grid for cost effective provisioning of electricity /	621.39 Segmentation of coronary arteries and detection of stenosis for CT angiographic images /	Next

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