Thesis (Ph. D.)--Ohio State University, 2007.

Thesis (Ph. D.)--Rutgers University, 2007. / "Graduate Program in Toxicology." Includes bibliographical references (p. 115-131).

Thesis (Ph. D.)--University of Montana, 2006. / Mode of access: Internet. Title from title screen. Description based on contents viewed Sept. 11, 2006. Includes bibliographical references (p. 153-170).

Thesis (Ph.D.)--University of Florida, 2005. / Typescript. Title from title page of source document. Document formatted into pages; contains 169 pages. Includes Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Missouri--Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 179-198). Also issued on the Internet.

DNA-binding proteins play an important role in various essential biological processes such as DNA replication, recombination, repair, gene transcription, and expression. The identification of DNA-binding proteins and the residues involved in the contacts is important for understanding the DNA-binding mechanism in proteins. Moreover, it has been reported in the literature that the mutations of some DNA-binding residues on proteins are associated with some diseases. The identification of these proteins and their binding mechanism generally require experimental techniques, which makes large scale study extremely difficult. Thus, the prediction of DNA-binding proteins and their binding sites from sequences alone is one of the most challenging problems in the field of genome annotation. Since the start of the human genome project, many attempts have been made to solve the problem with different approaches, but the accuracy of these methods is still not suitable to do large scale annotation of proteins. Rather than relying solely on the existing machine learning techniques, I sought to combine those using novel “stacking technique” and used the problem-specific architectures to solve the problem with better accuracy than the existing methods. This thesis presents a possible solution to the DNA-binding proteins prediction problem which performs better than the state-of-the-art approaches.

Thesis (Ph. D.)--Cornell University, August, 2006. / Vita. Includes bibliographical references (leaves 116-123).

Thesis (Ph. D.)--University of Washington, 2001. / Vita. Includes bibliographical references (leaves 171-177).

Thesis (Ph.D.)--University of Western Sydney, 2008. / A thesis presented to the University of Western Sydney, College of Health and Science, School of Biomedical and Health Sciences, in fulfilment of the requirements for the degree of Doctor of Philosophy. Includes bibliographies.

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 78-86).