Automating Genomic Data Mining via a Sequence-based Matrix Format and Associative Rule Set

There is an enormous amount of information encoded in each genome – enough to create living, responsive and adaptive organisms. Raw sequence data alone is not enough to understand function, mechanisms or interactions. Changes in a single base pair can lead to disease, such as sickle-cell anemia, while some large megabase deletions have no apparent phenotypic effect. Genomic features are varied in their data types and annotation of these features is spread across multiple databases. Herein, we develop a method to automate exploration of genomes by iteratively exploring sequence data for correlations and building upon them. First, to integrate and compare different annotation sources, a sequence matrix (SM) is developed to contain position-dependant information. Second, a classification tree is developed for matrix row types, specifying how each data type is to be treated with respect to other data types for analysis purposes. Third, correlative analyses are developed to analyze features of each matrix row in terms of the other rows, guided by the classification tree as to which analyses are appropriate. A prototype was developed and successful in detecting coinciding genomic features among genes, exons, repetitive elements and CpG islands

Photometric and Spectroscopic Observations of SN 1990E in NGC 1035: Observational Constraints for Models of Type II Supernovae

We present 126 photometric and 30 spectral observation of SN 1990E spanning from 12 days before B maximum to 600 days past discovery. These observations show that SN 1990E was of type II-P, displaying hydrogen in its spectrum, and the characteristic plateau in its light curve. SN 1990E is one of the few SNe II which has been well observed before maximum light, and we present evidence that this SN was discovered very soon after its explosion. In the earliest spectra we identify, for the first time, several N II lines. We present a new technique for measuring extinction to SNe II based on the evolution of absorption lines, and use this method to estimate the extinction to SN 1990E, Av=1.5+/-0.3 mag. From our photometric data we have constructed a bolometric light curve for SN 1990E and show that, even at the earliest times, the bolometric luminosity was falling rapidly. We use the late-time bolometric light curve to show that SN 1990E trapped a majority of the gamma rays produced by the radioactive decay of 56Co, and estimate that SN 1990E ejected 0.073 Mo of 56Ni, an amount virtually identical to that of SN 1987A. [excerpt

The Challenge of Massively Parallel Computing

Since the mid-1980's, there have been a number of commercially available parallel computers with hundreds or thousands of processors. These machines have provided a new capability to the scientific community, and they been used successfully by scientists and engineers although with varying degrees of success. One of the reasons for the limited success is the difficulty, or perceived difficulty, in developing code for these machines. In this paper we discuss many of the issues and challenges in developing scalable hardware, system software and algorithms for machines comprising hundreds or thousands of processors

The Torus--Wrap Mapping For Dense Matrix Calculations On Massively Parallel Computers

. Dense linear systems of equations are quite common in science and engineering, arising in boundary element methods, least squares problems and other settings. Massively parallel computers will be necessary to solve the large systems required by scientists and engineers, and scalable parallel algorithms for the linear algebra applications must be devised for these machines. A critical step in these algorithms is the mapping of matrix elements to processors. In this paper, we study the use of the torus--wrap mapping in general dense matrix algorithms, from both theoretical and practical viewpoints. We prove that, under reasonable assumptions, this assignment scheme leads to dense matrix algorithms that achieve (to within a constant factor) the lower bound on interprocessor communication. We also show that the torus--wrap mapping allows algorithms to exhibit less idle time, better load balancing and less memory overhead than the more common row and column mappings. Finally, we discuss ..

The Torus-Wrap Mapping For Dense Matrix Calculations On Massively Parallel Computers

Dense linear systems of equations are quite common in science and engineering, arising in boundary element methods, least squares problems and other settings. Massively parallel computers will be necessary to solve the large systems required by scientists and engineers, and scalable parallel algorithms for the linear algebra applications must be devised for these machines. A critical step in these algorithms is the mapping of matrix elements to processors. In this paper, we study the use of the torus--wrap mapping in general dense matrix algorithms, from both theoretical and practical viewpoints. We prove that, under reasonable assumptions, this assignment scheme leads to dense matrix algorithms that achieve (to within a constant factor) the lower bound on interprocessor communication. We also show that the torus--wrap mapping allows algorithms to exhibit less idle time, better load balancing and less memory overhead than the more common row and column mappings. Finally, we discuss ..

Salvo: Seismic imaging software for complex geologies

This report describes Salvo, a three-dimensional seismic-imaging software for complex geologies. Regions of complex geology, such as overthrusts and salt structures, can cause difficulties for many seismic-imaging algorithms used in production today. The paraxial wave equation and finite-difference methods used within Salvo can produce high-quality seismic images in these difficult regions. However this approach comes with higher computational costs which have been too expensive for standard production. Salvo uses improved numerical algorithms and methods, along with parallel computing, to produce high-quality images and to reduce the computational and the data input/output (I/O) costs. This report documents the numerical algorithms implemented for the paraxial wave equation, including absorbing boundary conditions, phase corrections, imaging conditions, phase encoding, and reduced-source migration. This report also describes I/O algorithms for large seismic data sets and images and parallelization methods used to obtain high efficiencies for both the computations and the I/O of seismic data sets. Finally, this report describes the required steps to compile, port and optimize the Salvo software, and describes the validation data sets used to help verify a working copy of Salvo