Construct a grid computing environment for bioinformatics

GOblet is a comprehensive web server application providing the annotation of anonymous sequence data with Gene Ontology (GO) terms. It uses a variety of different protein databases (human, murines, invertebrates, plants, sp-trembl) and their respective GO mappings. The user selects the appropriate database and alignment threshold and thereafter submits single or multiple nucleotide or protein sequences. Results are shown in different ways, e.g. as survey statistics for the main GO categories for all sequences or as detailed results for each single sequence that has been submitted. In its newest version, GOblet allows the batch submission of sequences and provides an improved display of results with the aid of Java applets. All output data, together with the Java applet, are packed to a downloadable archive for local installation and analysis. GOblet can be accessed freely at http://goblet.molgen.mpg.de.

This paper introduces a caching enabled parallel multi-objective tri-level particle swarm optimization algorithm (MO-3LPPSO) with objective to address a challenging NP-hard problem from bioinformatics i.e. structural alignment of complex RNA sequences. MO-3LPPSO implements master-slave topology based communication strategy on the parallely connected machines via message passing interface (MPI). Level 1 of the proposed algorithm acquires the optimal alignment of the sequences distributed on slave processors in the order of their complexities. Further, the aligned sequences along with their alignment scores are stored on the master processor. In the second level, the secondary structures of all the gbest aligned sequences of level 1 is obtained. Each sequence set is distributed on a slave processors, that constructs secondary structure of all sequences from the set. The alignment scores and secondary structure scores obtained from level 1 and level 2, now move towards level 3, forming a bi-objective optimization problem with the objectives to maximize sequence similarity score and minimize free energy score for most stable RNA secondary structure. The top-level non-dominated solutions are extracted further in level three and the external archive in Ctrie is updated. The improvement from MO-TLPSO to MO-3LPPSO has been remarkable in the sense: inclusion of Ctrie enables the algorithm to work with multi-client environment for handling RNA structural alignment queries; implementation of parallelization facilitates structural alignment of highly complex massive datasets of RNA sequences. Further, the difference between the time taken by MO-TLPSO and MO-3LPPSO is found extremely significant, as confirmed by non-parametric statistical test Mann-Whitney U test. Further, the structural alignment of highly complex sequence sets is performed by MO-3LPPSO, which is tested for prediction accuracy and processing time. The algorithm is found producing highly accurate results at significantly lesser processing time.

This chapter describes some approaches that have been proposed for access and usage control in grid systems. The first part of the chapter addresses the security challenges in grid systems and describes the standard security infrastructure provided by the Globus Toolkit, the most used middleware to establish grids. Since the standard Globus authorization system provides very basic mechanisms that do not completely fulfill the requirements of this environment, a short overview of well-known access control frameworks that have been integrated in Globus is also given: Community Authorization Service (CAS), PERMIS, Akenti, Shibboleth, Virtual Organization Membership Service (VOMS), Cardea, and PRIMA. Then, the chapter describes the usage control model UCON, a novel model for authorization, along with an implementation of UCON in grid systems. The last part of the chapter describes the authorization model for grid computational services designed by the Grid Trust project. This authorization model is also based on UCON.

wavepacket is a program to simulate the dynamics of a wave packet interacting with a time-dependent potential, with the time-dependent Schrödinger equation being solved on a one-, two-, or three-dimensional spatial grid using the split operator method. This new version fixes bugs present in the original program. New version program summaryProgram Title: wavepacketCPC Library link to program files:https://doi.org/10.17632/gnxmkygxrw.1Licensing provisions: GPLv3Programming language: C (iso C99)Journal reference of previous version: Comput. Phys. Commun. 185 (2014) 407–414.Does the new version supersede the previous version?: YesReasons for the new version: Bug fixes.Summary of revisions: This new version fixes bugs in the program wavepacket [1]. In the original version, the function print_wf_bin, used (optionally) to write out the wave function as a binary file, contained a bug that would result in only part of the full wave function being written out when the program was run in parallel.Additionally, negative values of the parameters nt and/or nprint could lead to the program being stuck in an infinite loop. Additional checks have been added to ensure that both these parameters are positive (or zero).Nature of problem: Solves the time-dependent Schrödinger equation for a single particle interacting with a time-dependent potential.Solution method: The wave function is described by its value on a spatial grid and the evolution operator is approximated using the split-operator method [2,3], with the kinetic energy operator calculated using a Fast Fourier Transform.Additional comments including restrictions and unusual features: Simulation can be in one, two, or three dimensions. The fftw [4] implementation of the fast Fourier transform is used, so the corresponding library must be installed. Serial and parallel versions are compiled from the same source files. The parallel version is based on the Message-Passing Interface (mpi) [5].

Exchanging and integration of patient data across heterogeneous databases and institutional boundaries offers many problems. We focused on two issues: (1) how to identify identical patients between different systems and institutions while lacking universal patient identifiers; and (2) how to link patient data across heterogeneous databases and institutional boundaries. To solve these problems, we created a patient identification (ID) translation model and a dynamic linking method in the Common Object Request Broker Architecture (CORBA) environment. The algorithm for the patient ID translation is based on patient attribute matching plus computer-based human checking; the method for dynamic linking is temporal mapping. By implementing these methods into computer systems with help of the distributed object computing technology, we built a prototype of a CORBA-based object framework in which the patient ID translation and dynamic linking methods were embedded. Our experiments with a Web-based user interface using the object framework and dynamic linking-through the object framework were successful. These methods are important for exchanging and integrating patient data across heterogeneous databases and institutional boundaries.

We propose a method to parallelize a 3D incompressible Navier–Stokes solver that uses a fully implicit fractional-step method to simulate sediment transport in prismatic channels. The governing equations are transformed into generalized curvilinear coordinates on a non-staggered grid. To develop a parallel version of the code that can run on various platforms, in particular on PC clusters, it was decided to parallelize the code using Message Passing Interface (MPI) which is one of the most flexible parallel programming libraries. Code parallelization is accomplished by “message passing” whereby the computer explicitly uses library calls to accomplish communication between the individual processors of the machine (e.g., PC cluster). As a part of the parallelization effort, besides the Navier–Stokes solver, the deformable bed module used in simulations with loose beds are also parallelized. The flow, sediment transport, and bathymetry at equilibrium conditions were computed with the parallel and serial versions of the code for the case of a 140-degree curved channel bend of rectangular section. The parallel simulation conducted on eight processors gives exactly the same results as the serial solver. The parallel version of the solver showed good scalability.

VisIt is a popular, free interactive parallel visualization and analysis tool for scientific data. Users can quickly generate visualizations from their data, animate them through time, manipulate them, and save the resulting images or movies for presentations. VisIt was designed from the ground up to work on many scales of computers from modest desktops up to massively parallel clusters. VisIt is comprised of a set of cooperating programs. All programs can be run locally or in client/server mode in which some run locally and some run remotely on compute clusters. The VisIt program most able to harness today's computing power is the VisIt compute engine. The compute engine is responsible for reading simulation data from disk, processing it, and sending results or images back to the VisIt viewer program. In a parallel environment, the compute engine runs several processes, coordinating using the Message Passing Interface (MPI) library. Each MPI process reads some subset of the scientific data and filters the data in various ways to create useful visualizations. By using MPI, VisIt has been able to scale well into the thousands of processors on large computers such as dawn and graph at LLNL. The advent of multicore CPU's has made parallelism the 'new' way to achieve increasing performance. With today's computers having at least 2 cores and in many cases up to 8 and beyond, it is more important than ever to deploy parallel software that can use that computing power not only on clusters but also on the desktop. We have created a parallel version of VisIt for Windows that uses Microsoft's MPI implementation (MSMPI) to process data in parallel on the Windows desktop as well as on a Windows HPC cluster running Microsoft Windows Server 2008. Initial desktop parallel support for Windows was deployed in VisIt 2.4.0. Windows HPC cluster support has been completed and will appear in the VisIt 2.5.0 release. We plan to continue supporting parallel VisIt on Windows so our users will be able to take full advantage of their multicore resources.

Thousands of putative open reading frames (ORFs) are identified via annotation of sequenced plant genomes. Classification of these ORFs into gene families has a crucial importance to understand the evolution, function, and structure of the encoded proteins such as transcription factors, and the non-coding RNAs such as microRNAs (miRNAs). Thus, molecular mechanisms underlying the metabolic processes in plants are uncovered as well. Some members of the gene families are species-specific being more dynamic during evolution whereas others are more conserved, phylogenetically sharing common features. The latter are especially important for the annotation of putative ORFs by revealing known counterparts with high sequence identity via sequence alignment to discover conserved motifs. Various bioinformatic tools are available to find out gene families in plants. The BLAST tool (http://blast.ncbi.nlm.nih.gov/Blast.cgi) is widely used for identification of homologous sequences. Phytozome (http://www.phytozome.net) or GreenPhyl (http://www.greenphyl.org) are the web resources utilized for the functional and comparative genomics in plants to analyze gene families. TRAPID (http://bioinformatics.psb.ugent.be/webtools/trapid) offers a free of charge web source for functional and comparative analyses of transcriptome data sets for identification of gene families, alignment of multiple sequences and phylogenetic tree construction. Some of the databases store specific type of gene families such as plant transcription factor databases PlantTFDB (http://planttfdb.cbi.pku.edu.cn) and PlnTFDB (http://plntfdb.bio.uni-potsdam.de/v3.0), or miRBase (http://www.mirbase.org) for miRNAs. Molecular Evolutionary Genetics Analysis (MEGA) software is an integrated tool for the analyses such as alignment of sequence, construction of phylogenetic trees, and access to online databases. In this chapter, the bioinformatic tools for analyses of genomics and/or transcriptomics data sets to discover gene families as well as sample researches are discussed.

We have built a Debian-Beowulf computer cluster consisting of 15 computational nodes, each equipped with 15 AMD Opteron 64 bit microprocessors. Local Area Multicomputer (LAM) - Message Passing Interface (MPI) was used as a portable high-performance implementation for MPI. More than 2,000 bacterial 16S ribosomal RNAs (rRNAs) were multiply aligned using ClustalW-MPI. Systematic sequence comparison provided several sequences with a very high degree of homology despite their different origins of species. These highly conservative sequences were collected as candidate sequences for drug targets of ribosomal antibiotics.

A cluster is a collection of independent and cheap machines, used together as a supercomputer to provide a solution. A PC cluster consisting of one master node and nine disk-less slave nodes (10 processors), is proposed and built for parallel rendering purposes. The system architecture and benchmark performances of this cluster are also presented. Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. Harnessing these new technologies effectively will transform scientific disciplines ranging from high-energy physics to the life sciences. Also, We construct two heterogeneous PC clusters for parallel rendering purpose and install Linux Red Hat 9 on each PC cluster. Then, these clusters are set to the different subnet. Therefore, we use the grid middleware /spl lambda/obus ToolKit, to connect these two clusters to form a grid computing environment on multiple Linux PC clusters. We also install the SUN Grid Engine, to manage and monitor incoming or outgoing computing jobs and schedule the job to achieve high performance computing and high CPU utilization. The system architecture and benchmark performances of this cluster are also presented.

Grid security solutions address critical requirements and are constructed from building blocks comprising cryptographic algorithms and protocols. Choosing the most appropriate algorithms and protocols requires an ongoing evaluation of performance and security properties, given continuing advances in system performance, optimizations, security analyses, and cryptographic techniques. Today, the Globus Toolkit's grid security infrastructure (GSI) is a leading provider of security solutions based on the RSA cryptosystem. Recently, cryptosystems based on bilinear pairings have been proposed as an alternative with the promise of increased efficiency and scalability. In this work we evaluate this alternative compared to elliptic curve cryptography (ECC) and RSA in terms of their computation and communication overheads for today's grid systems. Our analysis and experiments lead us to conclude that RSA continues to be a good choice for the foreseeable future. Furthermore, our results are intuitively aligned with the high-performance, high-bandwidth, and high-latency nature of grid systems.

Computer generated sequence alignment became a conventional tool in bioinformatics. SIM is one of the methods for determining similarity between two sequences through a pair-wise sequence alignment. However, most of the conventional tools lack the ability of incorporating biological properties into the alignment result which often leads to incorrect alignment. In this paper, we used a pair-wise alignment system called SIM that incorporates biological properties into the algorithm so that it can suggest an appropriate sequence alignment based on the given nucleotide base pairs. SIM indicated nucleotide sequences alignments and suggested massive rearrangements of extra chromosomal, which can be extrapolated to total genome rearrangements.

Understanding how one sequence relates to another at the nucleotide or amino acid level allows the derivation of new knowledge regarding the provenance of particular sequence as well as the determination of consensus sequence motifs that informs biological conservation at the sequence level. To this end, local or multiple sequence alignments tools in bioinformatics have been developed to automatically profile two or more nucleotide or amino acid sequence in search of matches in stretches of nucleotides or amino acid sequence that yield an alignment. While alignment score is a common metric for assessing alignment quality, relative difference between alignment scores does not readily correlate with concrete measures such as number of mismatches and length of longest match in alignment. Thus, using swalign local sequence alignment function in MATLAB on 200 alignments between RNA-seq sequence read and reference Escherichia coli K-12 MG1655 genome sequence in the sense and antisense direction, this work sought to shed some light on how alignment score from swalign correlates with number of mismatches and length of longest match. Results revealed that number of mismatches negatively correlate with alignment score; thereby, validating theoretical predictions that larger number of mismatches would result in a poorer alignment and lower alignment score. However, dependence of alignment score on other factors such as length of longest match and gap penalty from opening an alignment gap prevents linear relationship to be obtained between number of mismatches and alignment score. On the other hand, length of longest match was found to positively correlate with alignment score as predicted from theoretical understanding. But, data obtained revealed that clusters of data points gather at two regions of the scatter plot involving short matches and low alignment score, as well as long matches and high alignment score. Such clustering and sparseness of data points between the two clusters preclude the elucidation of a linear quantitative relationship between length of longest match and alignment score. Overall, dependence of alignment score of swalign on number of mismatches and length of longest match in alignment match theoretical predictions; thereby, validating the utility of alignment score in indicating the qualitative quality of alignment. However, given that alignment score inherently depends on a multitude of factors, users could not easily discern the quantitative difference in mismatches and length of longest match from relative differences between two alignment scores. Such problems are unlikely to be resolved given the near impossibility of obtaining quantitative linear relationship correlating either number of mismatches or length of longest match with alignment score of a sequence alignment tool.

The Reservoir GeoMechanics Simulator (RGMS), a geomechanics simulator based on the finite element method and parallelized using the Message Passing Interface (MPI), is developed in this work to model the stresses and deformations in subsurface systems. RGMS can be used stand-alone, or coupled with flow and transport models. pT+H V1.5, a parallel MPI-based version of the serial T+H V1.5 code that describes mass and heat flow in hydrate-bearing porous media, is also developed. Using the fixed-stress split iterative scheme, RGMS is coupled with the pT+H V1.5 to investigate the geomechanical responses associated with gas production from hydrate accumulations. The code development and testing process involve evaluation of the parallelization and of the coupling method, as well as verification and validation of the results. The parallel performance of the codes is tested on the Ada Linux cluster of the Texas A&M High Performance Research Computing using up to 512 processors, and on a Mac Pro computer with 12 processors. The investigated problems are: Group 1: Geomechanical problems solved by RGMS in 2D Cartesian and cylindrical domains and a 3D problem, involving 4x106 and 3.375 x106 elements, respectively; Group 2: Realistic problems of gas production from hydrates using pT+H V1.5 in 2D and 3D systems with 2.45x105 and 3.6 x106 elements, respectively; Group 3: The 3D problem in Group 2 solved with the coupled RGMS-pT+H V1.5 simulator, fully accounting for geomechanics. Two domain partitioning options are investigated on the Ada Linux cluster and the Mac Pro, and the code parallel performance is monitored. On the Ada Linux cluster using 512 processors, the simulation speedups (a) of RGMS are 218.89, 188.13, and 284.70 in the Group 1 problems, (b) of pT+H V1.5 are 174.25 and 341.67 in the Group 2 cases, and (c) of the coupled simulators is 331.80 in Group 3. The results produced in this work show the necessity of using full geomechanics simulators in marine hydrate-related studies because of the associated pronounced geomechanical effects on production and displacements and (b) the effectiveness of the parallel simulators developed in this study, which can be the only realistic option in these complex simulations of large multi-dimensional domains.

Unlocking massively parallel spectral proper orthogonal decompositions in the PySPOD package