43737883
Translation Initiation Sites Prediction with Mixture Gaussian Models
Translation initiation sites (TIS) are important signals in cDNA sequences. Many research efforts have tried to predict TIS in cDNA sequences. In this paper, we propose using mixture Gaussian models to predict TIS in cDNA sequences. Some new global measures are used to generate numerical features from cDNA sequences, such as the length of the open reading frame downstream from ATG, the number of other ATGs upstream and downstream from the current ATGs, etc. With these global features, the proposed method predicts TIS with sensitivity 98% and specificity 92%. The sensitivity is much better than that from other methods. We attribute the improvement in sensitivity to the nature of the global features and the mixture Gaussian models.
14226296
Translation initiation sites prediction with mixture Gaussian models in human cDNA sequences
Translation initiation sites (TISs) are important signals in cDNA sequences. Many research efforts have tried to predict TISs in cDNA sequences. In this paper, we propose to use mixture Gaussian models for TIS prediction. Using both local features and some features generated from global measures, the proposed method predicts TISs with a sensitivity of 98 percent and a specificity of 93.6 percent. Our method outperforms many other existing methods in sensitivity while keeping specificity high. We attribute the improvement in sensitivity to the nature of the global features and the mixture Gaussian models.
16653782
Genetic Algorithm Based on Independent Component Analysis for Global Optimization
We design a new Genetic Algorithm based on Independent Component Analysis for unconstrained global optimization of continuous function. We use Independent Component Analysis to linearly transform the original dimensions of the problem into new components which are independent from each other with respect to the fitness. We project the population on the independent components and obtain corresponding sub-populations. We apply genetic operators on the sub-populations to generate new sub-populations, and combine them as a new population. In other words, we use Genetic Algorithm to find the optima on the independent components, and combine the optima as the global optimum for the problem. As we actually reduce the original high-dimensional problem into sub-problems of much fewer dimensions, the solution space decreases exponentially and thus the problem becomes easier for Genetic Algorithm to solve. The experiment results verified that our algorithm produced optimal or close-to-optimal solutions better than or comparable to those produced by some of other Genetic Algorithms and it required much less fitness evaluations of individuals.
8483401
Optimum spatial-temporal receiver for wireless systems with ISI and CCI
Spatial-temporal processing is an effective technique for wireless systems with antenna arrays to suppress co-channel interference. In this paper, spatial-temporal receive filters for multiple receiver systems with intersymbol interference (ISI), co-channel interference (CCI), and additive white Gaussian noise (AWGN) are investigated. An analogical spatial-temporal matched filter that is optimum for any following T-spaced processor with any reasonable criterion of goodness is found. Therefore, it allows co-channel interference suppression and equalization to be treated separately.
11626813
Sorting Signed Permutations by Fixed-length Reversals
A signed n-permutation is a permutation on {1,2,…,n} in which each element is labelled by a positive or negative sign. Here we consider the problem of sorting signed permutations by fixed-length reversals. Indeed, limiting the transformations to reversals of length exactly k can be very restrictive, for example, (+1,+3,+2,+4,…,+n) can never be sorted to (+1,+2,+3,+4,…,+n) by 2-reversals. That is, for given two signed permutations it is not obvious whether they can be sorted to each other by k-reversals. Thus in 1996, Chen and Skiena gave the following open problem: what is the connectedness of signed permutations under fixed-length reversals? In this paper, we resolve this open problem when "fixed-length" is even, and give a characterization of the connectedness of signed n-permutations under 2l-reversal, for both linear and circular permutations.
664043
Evolutionary structure learning algorithm for Bayesian network and Penalized Mutual Information metric
The paper formulates the problem of learning Bayesian network structures from data as determining the structure that best approximates the probability distribution indicated by the data. A new metric, Penalized Mutual Information metric, is proposed, and an evolutionary algorithm is designed to search for the best structure among alternatives. The experimental results show that this approach is reliable and promising.
109807
One table stores all: Enabling painless free-and-easy data publishing and sharing
In this paper, we present a free-and-easy data publishing and sharing system based on folksonomy. The system accepts data objects described with user-created metadata, called data units. The system supports flexible structure on the data units, and places no restrictions on the vocabulary used. We devise a generic table model for storing and representing the data units of various structures. We propose a framework for managing the data units and providing browsing, searching and querying services over them. We present our current approaches and discuss relevant research issues.