Thesis (Ph. D.)--University of Washington, 1999. / Vita. Includes bibliographical references (leaves 131-157).

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (p. 85-102).

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (p. 83-102).

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (leaves 121-140).

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (leaves 122-146).

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (p. 105-112).

>Magister Scientiae - MSc / The study area for this thesis focuses on the central northern part of the Bredasdorp Basin of southern offshore South Africa, where the depositional environments of wells E-M1, E-M3 and E-AB1 were inferred through electro sequence analysis and sequence stratigraphy analysis of the corresponding seismic line (E82-005). For that, the Petroleum Agency of South Africa (PASA) allowed access to the digital data which were loaded onto softwares such as PETREL and Kingdom SMT for interpretational purposes. The lithologies and sedimentary environments were inferred based on the shape of the gamma ray logs and reported core descriptions. The sequence stratigraphy of the basin comprises three main tectonic phases: Synrift phase, Transitional phase and Drift phase. Syn-rift phase, which began in the Middle Jurassic during a period of regional tectonism, consists of interbedded red claystones and discrete pebbly sandstone beds deposited in a non-marine setting. The syn-rift 1 succession is truncated by the regional Horizon ‘C’ (1At1 unconformity). The transitional phase was influenced by tectonic events, eustatic sea-level changes and thermal subsidence and characterized by repeated episodes of progradation and aggradation between 121Ma to 103Ma, from the top of the Horizon ‘C’ (1At1 unconformity) to the base of the 14At1 unconformity. Finally the drift phase was driven by thermal subsidence and marked by the Middle Albian14At1 unconformity which is associated with deep water submarine fan sandstones. During the Turonian (15At1 unconformity), highstand led to the deposition of thin organic-rich shales. In the thesis, it is concluded that the depositional environment is shallow marine, ranging from prograding marine shelf, a transgressive marine shelf and a prograding shelf edge delta environment.

No description available.

No description available.

Unlike tRNAs and microRNAs, both classes of snoRNAs, which direct two distinct types of chemical modifications of uracil residues, have proved to be surprisingly difficult to find in genomic sequences. Most computational approaches so far have explicitly used the fact that snoRNAs predominantly target ribosomal RNAs and spliceosomal RNAs. The target is specified by a short stretch of sequence complementarity between the snoRNA and its target. This sequence complementarity to known targets crucially contributes to sensitivity and specificity of snoRNA gene finding algorithms. The discovery of ‘orphan’ snoRNAs, which either have no known target, or which target ordinary protein-coding mRNAs, however, begs the question whether this class of ‘housekeeping’ non-coding RNAs is much more widespread and might have a diverse set of regulatory functions. In order to approach this question, we present here a combination of RNA secondary structure prediction and machine learning that is designed to recognize the two major classes of snoRNAs, box C/D and box H/ACA snoRNAs, among ncRNA candidate sequences. The snoReport approach deliberately avoids any usage of target information. We find that the combination of the conserved sequence boxes and secondary structure constraints as a pre-filter with SVM classifiers based on a small set of structural descriptors are sufficient for a reliable identification of snoRNAs. Tests of snoReport on data from several recent experimental surveys show that the approach is feasible; the application to a dataset from a large-scale comparative genomics survey for ncRNAs suggests that there are likely hundreds of previously undescribed ‘orphan’ snoRNAs still hidden in the human genome.