Algorithms for detection of modules in genetics interaction networks, while often identifying new models of functional modular organization between genes, have been limited to the output of disjoint, non-overlapping modules, while natural overlapping modules have been observed in biological networks. We present CLOVER, an algorithm for clustering weighted networks into overlapping clusters. We ...

The Adaptive Multiple Importance Sampling (AMIS) algorithm is aimed at an optimal recycling of past simulations in an iterated importance sampling scheme. The difference with earlier adaptive importance sampling implementations like Population Monte Carlo is that the importance weights of all simulated values, past as well as present, are recomputed at each iteration, following the technique of...

This paper proposes a Hybrid Genetic Algorithm (HGA) for the Resource Constrained Project Scheduling Problem (RCPSP). Resources are renewable and there is a unique way to perform the activities. This work employs Genetics Algorithms (GA) and Hybrid Genetic Algorithms to schedule project activities to minimize makespan subject to precedence constraints and resources availability. The algorithms ...

ALPINE is to our knowledge the first anytime algorithm to mine frequent itemsets and closed frequent itemsets. It guarantees that all itemsets with support exceeding the current checkpoint’s support have been found before it proceeds further. Thus, it is very attractive for extremely long mining tasks with very high dimensional data (for example in genetics) because it can offer intermediate me...

We describe the application of a hybrid symbolic/connectionist machine learning algorithm to the task of recognizing important genetic sequences. The symbolic portion of the KBANN system utilizes inference rules that provide a roughly-correct method for recognizing a class of DNA sequences known as eukaryotic splice-junctions. We then map this "domain theory" into a neural network and provide t...

Sequential techniques can enhance the efficiency of the approximate Bayesian computation algorithm, as in Sisson et al.’s (2007) partial rejection control version. While this method is based upon the theoretical works of Del Moral et al. (2006), the application to approximate Bayesian computation results in a bias in the approximation to the posterior. An alternative version based on genuine im...

Current and voltage waveforms of a distribution or a transmission system are not pure sinusoids. There are distortions in these waveforms that consist of a combination of the fundamental frequency, harmonics and high frequency transients. This paper presents an enhanced measurement scheme for identification and tracking of harmonics in power system. The proposed technique is not limited to stat...

In this paper, we present a fast and simple algorithm for constructing a minimal acyclic deterministic finite automaton from a finite set of words. Such automata are useful in a wide variety of applications, including computer virus detection, computational linguistics and computational genetics. There are several known algorithms that solve the same problem, though most of the alternative algo...

Recombination plays an important role in creating genetic diversity within species, and inferring past recombination events is central to many problems in genetics. Given a set M of sampled sequences, finding an evolutionary history for M with the minimum number of recombination events is a computationally very challenging problem. In this paper, we present a novel branch and bound algorithm fo...

In the past decade computational biology has grown from a cottage industry with a handful of researchers to an attractive interdisciplinary field, catching the attention and imagination of many quantitatively-minded scientists. Of interest to us is the key role played by the EM algorithm during this transformation. We survey the use of the EM algorithm in a few important computational biology p...