A global function for transcription factors in assisting RNA polymerase II termination.

The role of transcription factors (TFs) on nucleosome positioning, RNA polymerase recruitment, and transcription initiation has been extensively characterized. Here, we propose that a subset of TFs such as Reb1, Abf1, Rap1, and TFIIIB also serve a major function in partitioning transcription units by assisting the Nrd1p-Nab3p-Sen1p Pol II termination pathway

SMART WALL OUTLET DESIGN AND IMPLEMENTATION FOR THE DC HOUSE PROJECT

Most everyday AC appliances are designed to operate off of 120V coming from the wall outlet in our homes. This voltage is a standard set from our established infrastructure. Unlike AC devices, DC devices do not have any set standard of voltage they all will run off of. This presents a problem for the DC house as the various loads that will be used will have different required input voltages. One set voltage for a wall outlet will not suffice for the DC House. This Smart Wall Outlet is designed with a DC-DC converter that will have its output voltage controlled by an on-board microprocessor. The Smart Wall Outlet detects current going into a device, and will adjust the voltage applied to the device to ensure it operates most efficiently. Proof of concept research has already been performed in the past, and this thesis will look towards implementing this concept on a single circuit board

SLIQ: Simple Linear Inequalities for Efficient Contig Scaffolding

Scaffolding is an important subproblem in "de novo" genome assembly in which mate pair data are used to construct a linear sequence of contigs separated by gaps. Here we present SLIQ, a set of simple linear inequalities derived from the geometry of contigs on the line that can be used to predict the relative positions and orientations of contigs from individual mate pair reads and thus produce a contig digraph. The SLIQ inequalities can also filter out unreliable mate pairs and can be used as a preprocessing step for any scaffolding algorithm. We tested the SLIQ inequalities on five real data sets ranging in complexity from simple bacterial genomes to complex mammalian genomes and compared the results to the majority voting procedure used by many other scaffolding algorithms. SLIQ predicted the relative positions and orientations of the contigs with high accuracy in all cases and gave more accurate position predictions than majority voting for complex genomes, in particular the human genome. Finally, we present a simple scaffolding algorithm that produces linear scaffolds given a contig digraph. We show that our algorithm is very efficient compared to other scaffolding algorithms while maintaining high accuracy in predicting both contig positions and orientations for real data sets.Comment: 16 pages, 6 figures, 7 table