Articles via Databases
Articles via Journals
Online Catalog
E-books
Research & Information Literacy
Interlibrary loan
Theses & Dissertations
Collections
Policies
Services
About / Contact Us
Administration
Littman Architecture Library
This site will be removed in January 2019, please change your bookmarks.
This page will redirect to https://digitalcommons.njit.edu/theses/1034 in 5 seconds

The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title: Testing statistical significance in sequence classification algorithms
Author: Shih, Tom Tien-Hua
View Online: njit-etd1997-090
(iv, 26 pages ~ 1.0 MB pdf)
Department: Department of Computer and Information Science
Degree: Master of Science
Program: Computer Science
Document Type: Thesis
Advisory Committee: Wang, Jason T. L. (Committee chair)
McHugh, James A. (Committee member)
Ng, Peter A. (Committee member)
Date: 1997-10
Keywords: Proteins--Analysis.
Algorithms.
Combinatorial optimization.
Availability: Unrestricted
Abstract:

Multiple sequence alignment has proven to be a successful method of representing and organizing of protein sequence data. It is crucial to medical researches on the structure and function of proteins.

There have been numerous tools published on how to abstract meaningful relationship from an unknown sequence and a set of known sequences. One study used a method for discovering active motifs in a set of related protein sequences. These are meaningful knowledge abstracted from the known protein database since most protein families are characterized by multiple local motifs. Another study abstracts knowledge regarding the input sequence using a preconstructed algorithm from a set of sequences.

Most of these studies of classification processes use statistically optimized heuristics to enhance their accompanying algorithms. Therefore, these algorithms can be analyzed for statistical significance using Baysian Theorems.


If you have any questions please contact the ETD Team, libetd@njit.edu.

 
ETD Information
Digital Commons @ NJIT
Theses and DIssertations
ETD Policies & Procedures
ETD FAQ's
ETD home

Request a Scan
NDLTD

NJIT's ETD project was given an ACRL/NJ Technology Innovation Honorable Mention Award in spring 2003