In silico prediction of non-coding RNAs using supervised learning and feature ranking methods

This thesis presents a novel method, RNAMultifold, for development of a non-coding RNA (ncRNA) classification model based on features derived from folding the consensus sequence of multiple sequence alignments using different folding programs: RNAalifold, CentroidFold, and RSpredict. The method ranks these folding features according to a Class Separation Measure (CSM) that quantifies the ability of the features to differentiate between samples from positive and negative test sets. The set of top-ranked features is then used to construct classification models: Naive Bayes, Fisher Linear Discriminant, and Support Vector Machine (SVM). These models are compared to the performance of the same models with a baseline feature set and with an existing classification tool, RNAz. The Support Vector Machine classification model with a radial basis function kernel, using the top 11 ranked features, is shown to be more sensitive than other models, including another ncRNA prediction program, RNAz, across all specificity values for the RNA families under study. In addition, the target feature set outperforms the baseline feature set of z score and structure conservation index across all classification methods, with the exception of Fisher Linear Discriminant. The RNAMultifold method is then used to search the genome of a Trypanosome species (Trypanosoma brucei) for novel ncRNAs. The results of this search are compared with known ncRNAs and with results from RNAz

Bounds on Differential and Linear Branch Number of Permutations

Nonlinear permutations (S-boxes) are key components in block ciphers. The differential branch number measures the diffusion power of a permutation, whereas the linear branch number measures resistance against linear cryptanalysis. There has not been much analysis done on the differential branch number of nonlinear permutations of $\mathbb{F}_2^n$, although it has been well studied in case of linear permutations. Similarly upper bounds for the linear branch number have also not been studied in general. In this paper we obtain bounds for both the differential and the linear branch number of permutations (both linear and nonlinear) of $\mathbb{F}_2^n$. We also prove that in the case of $\mathbb{F}_2^4$, the maximum differential branch number can be achieved only by affine permutations

Asymmetric first-price auctions with uniform distributions: analytic solutions to the general case

While auction research, including asymmetric auctions, has grown significantly in recent years, there is still little analytical solutions of first-price auctions outside the symmetric case. Even in the uniform case, Griesmer et al. (1967) and Plum (1992) find solutions only to the case where the lower bounds of the two distributions are the same. We present the general analytical solutions to asymmetric auctions in the uniform case for two bidders, both with and without a minimum bid. We show that our solution is consistent with the previously known solutions of auctions with uniform distributions. Several interesting examples are presented including a class where the two bid functions are linear. We hope this result improves our understanding of auctions and provides a useful tool for future research in auctions

Less Bone Loss With Maraviroc- Versus Tenofovir-Containing Antiretroviral Therapy in the AIDS Clinical Trials Group A5303 Study

Background. There is a need to prevent or minimize bone loss associated with antiretroviral treatment (ART) initiation. We compared maraviroc (MVC)- to tenofovir disoproxil fumarate (TDF)–containing ART