Probabilistic inductive logic programming (PILP), sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integration of probabilistic reasoning with first order logic representations and machine learning. A rich variety of different formalisms and learning techniques have been developed and they are being applied on applicat...

Processing of next-generation sequencing (NGS) data requires significant technical skills, involving installation, configuration, and execution of bioinformatics data pipelines, in addition to specialized postanalysis visualization and data mining software. In order to address some of these challenges, developers have leveraged virtualization containers toward seamless deployment of preconfigur...

Sequence alignment is the most basic and essential module of computational bio-informatics. In this paper, we propose a multiple sequence alignment algorithm that employs fuzzy logic to measure the similarity of sequences based on fuzzy parameters. To guarantee the optimal alignment of the sequences, dynamic programming is used to align the sequences. The algorithm is tested on few sets of real...

Bio: I am a first year PhD student in the Computer Science Department at UC Berkeley. I am advised by James Demmel and Armando Fox. My research interests include numerical linear algebra, high performance computing, and programming languages and tools. Application areas of interest include computational materials science and computational epidemiology. I am taking this course to further my know...

Bio: Ravi Jain received the Ph. D in Computer Science from the University of Texas at Austin in 1992. Prior to that he worked at Syntrex Inc., SES Inc. and the Schlumberger Laboratory for Computer Science on developing communications and systems software, performance modeling, and parallel programming. Since 1992 he has been a Research Scientist and then a Senior Scientist in Applied Research, ...

An important challenge in bioinformatics is to leverage different descriptions of the same data set, each capturing different aspects of the data. Many such sources of information [about genes and proteins] are now available, such as sequence,

Modern life sciences are becoming increasingly data intensive, posing a significant challenge for most researchers and shifting the bottleneck of scientific discovery from data generation to data analysis. As a result, progress in genome research is increasingly impeded by bioinformatic hurdles. A new generation of powerful and easy-to-use genome analysis tools has been developed to address thi...

Since the discovery of microRNAs (miRNAs), a class of noncoding RNAs that regulate the gene expression posttranscriptionally in sequence-specific manner, there has been a release of number of tools useful for both basic and advanced applications. This is because of the significance of miRNAs in many pathophysiological conditions including cancer. Numerous bioinformatics tools that have been dev...

String comparison is a critical issue in many application domains, including speech recognition, contents search, and bioinformatics. The similarity between two strings of lengths N and M can be computed in O(N × M) steps by means of a dynamic programming algorithm developed by Needleman and Wunsh. The algorithm can be effectively mapped onto a systolic array, resulting in a parallel implementa...

Swarming and modular robotic locomotion are two disconnected behaviours that a group of small homogeneous robots can be used to achieve. The use of these two behaviours is a popular subject in robotics research involving search, rescue and exploration. However, they are rarely addressed as two behaviours that can coexist within a single robotic system. Here, we present a bio-inspired decision m...