Prudence W. H. Wong

Filtering of ineffective siRNAs and improved siRNA design tool

MOTIVATION Short interfering RNAs (siRNAs) can be used to suppress gene expression and possess many potential applications in therapy, but how to design an effective siRNA is still not clear. Based on the MPI (Max-Planck-Institute) basic principles, a number of siRNA design tools have been developed recently. The set of candidates reported by these tools is usually large and often contains ineffective siRNAs. In view of this, we initiate the study of filtering ineffective siRNAs. RESULTS The contribution of this paper is 2-fold. First, we propose a fair scheme to compare existing design tools based on real data in the literature. Second, we attempt to improve the MPI principles and existing tools by an algorithm that can filter ineffective siRNAs. The algorithm is based on some new observations on the secondary structure, which we have verified by AI techniques (decision trees and support vector machines). We have tested our algorithm together with the MPI principles and the existing tools. The results show that our filtering algorithm is effective. AVAILABILITY The siRNA design software tool can be found in the website http://www.cs.hku.hk/~sirna/ CONTACT smyiu@cs.hku.hk

Parameter Estimation of Photovoltaic Models via Cuckoo Search

Since conventional methods are incapable of estimating the parameters of Photovoltaic (PV) models with high accuracy, bioinspired algorithms have attracted significant attention in the last decade. Cuckoo Search (CS) is invented based on the inspiration of brood parasitic behavior of some cuckoo species in combination with the Levy flight behavior. In this paper, a CS-based parameter estimation method is proposed to extract the parameters of single-diode models for commercial PV generators. Simulation results and experimental data show that the CS algorithm is capable of obtaining all the parameters with extremely high accuracy, depicted by a low Root-Mean-Squared-Error (RMSE) value. The proposed method outperforms other algorithms applied in this study.

Speed Scaling Functions for Flow Time Scheduling Based on Active Job Count

We study online scheduling to minimize flow time plus energy usage in the dynamic speed scaling model. We devise new speed scaling functions that depend on the number of active jobs, replacing the existing speed scaling functions in the literature that depend on the remaining work of active jobs. The new speed functions are more stable and also more efficient. They can support better job selection strategies to improve the competitive ratios of existing algorithms [8,5], and, more importantly, to remove the requirement of extra speed. These functions further distinguish themselves from others as they can readily be used in the non-clairvoyant model (where the size of a job is only known when the job finishes). As a first step, we study the scheduling of batched jobs (i.e., jobs with the same release time) in the non-clairvoyant model and present the first competitive algorithm for minimizing flow time plus energy (as well as for weighted flow time plus energy); the performance is close to optimal.

EFFICIENT CONSTRAINED MULTIPLE SEQUENCE ALIGNMENT WITH PERFORMANCE GUARANTEE

The Constrained Multiple Sequence Alignment problem is to align a set of sequences subject to a given constrained sequence, which arises from some knowledge of the structure of the sequences. This paper presents new algorithms for this problem, which are more efficient in terms of time and space (memory) than the previous algorithms [14], and with a worst-case guarantee on the quality of the alignment. Saving the space requirement by a quadratic factor is particularly significant as the previous O(n(4))-space algorithm has limited application due to its huge memory requirement. Experiments on real data sets confirm that our new algorithms show improvements in both alignment quality and resource requirements.

New Results on On-Demand Broadcasting with Deadline via Job Scheduling with Cancellation

This paper studies the on-demand broadcasting problem with deadlines. We give the first general upper bound and improve existing lower bounds on the competitive ratio of the problem. The novelty of our work is the introduction of a new job scheduling problem that allows cancellation. We prove that the broadcasting problem can be reduced to this scheduling problem. This reduction frees us from the complication of the broadcasting model and allows us to work on a conceptually simpler model for upper bound results.

New Structural and Functional Contexts of the Dx[DN]xDG Linear Motif: Insights into Evolution of Calcium-Binding Proteins

Binding of calcium ions (Ca2+) to proteins can have profound effects on their structure and function. Common roles of calcium binding include structure stabilization and regulation of activity. It is known that diverse families – EF-hands being one of at least twelve – use a Dx[DN]xDG linear motif to bind calcium in near-identical fashion. Here, four novel structural contexts for the motif are described. Existing experimental data for one of them, a thermophilic archaeal subtilisin, demonstrate for the first time a role for Dx[DN]xDG-bound calcium in protein folding. An integrin-like embedding of the motif in the blade of a β-propeller fold – here named the calcium blade – is discovered in structures of bacterial and fungal proteins. Furthermore, sensitive database searches suggest a common origin for the calcium blade in β-propeller structures of different sizes and a pan-kingdom distribution of these proteins. Factors favouring the multiple convergent evolution of the motif appear to include its general Asp-richness, the regular spacing of the Asp residues and the fact that change of Asp into Gly and vice versa can occur though a single nucleotide change. Among the known structural contexts for the Dx[DN]xDG motif, only the calcium blade and the EF-hand are currently found intracellularly in large numbers, perhaps because the higher extracellular concentration of Ca2+ allows for easier fixing of newly evolved motifs that have acquired useful functions. The analysis presented here will inform ongoing efforts toward prediction of similar calcium-binding motifs from sequence information alone.

Improved on-line broadcast scheduling with deadlines

We study an on-line broadcast scheduling problem in which requests have deadlines, and the objective is to maximize the weighted throughput, i.e., the weighted total length of the satisfied requests. For the case where all requested pages have the same length, we present an online deterministic algorithm named BAR and prove that it is 4.56-competitive. This improves the previous algorithm of Kim and Chwa [11] which is shown to be 5-competitive by Chan et al. [4]. In the case that pages may have different lengths, we prove a lower bound of Ω(Δ/logΔ) on the competitive ratio where Δ is the ratio of maximum to minimum page lengths. This improves upon the previous

Optimizing throughput and energy in online deadline scheduling

\sqrt{\Delta}

Energy efficient deadline scheduling in two processor systems

lower bound in [11,4] and is much closer to the current upper bound of (

Sleep with Guilt and Work Faster to Minimize Flow Plus Energy

\Delta+2\sqrt{\Delta}+2