Molecular docking is a computational technique which predicts the binding energy and the preferred binding mode of a ligand to a protein target. Virtual screening is a tool which uses docking to investigate large chemical libraries to identify ligands that bind favorably to a protein target. We have developed a novel scoring based distributed protein docking application to improve enrichment in virtual screening. The application addresses the issue of time and cost of screening in contrast to conventional systematic parallel virtual screening methods in two ways. Firstly, it automates the process of creating and launching multiple independent dockings on a high performance computing cluster. Secondly, it uses a Nȧi̇ve Bayes scoring function to calculate binding energy of un-docked ligands to identify and preferentially dock (Autodock predicted) better binders. The application was tested on four proteins using a library of 10,573 ligands. In all the experiments, (i). 200 of the 1,000 best binders are identified after docking only ~14 percent of the chemical library, (ii). 9 or 10 best-binders are identified after docking only ~19 percent of the chemical library, and (iii). no significant enrichment is observed after docking ~70 percent of the chemical library. The results show significant increase in enrichment of potential drug leads in early rounds of virtual screening.

A campus grid is a critical component of research cyberinfrastructure. A grid facilitates resource sharing, improving collaboration and increasing the capability to address large scale scientific and engineering problems. Resources comprising a grid include research clusters, centrally managed clusters, opportunistic use of desktop computers, campus clouds, and commercial clouds.

This paper describes "Computational Thinking for the Sciences", a 3-day summer workshop for high school science and mathematics teachers. Our workshop emphasizes the deep connections between the natural sciences, mathematics and computer science through activities and simulation development appropriate for scientific explorations. Teachers were exposed to simulation development in VPython, a visual extension to the popular Python programming language. By broadening exposure of computational thinking to the natural sciences and developing activities specifically for science domains, we hope to attract new students into computer science and better prepare natural science students to employ the computational tools they will utilize in the future.

BACKGROUND: Different classes of haplotype block algorithms exist and the ideal dataset to assess their performance would be to comprehensively re-sequence a large genomic region in a large population. Such data sets are expensive to collect. Alternatively, we performed coalescent simulations to generate haplotypes with a high marker density and compared block partitioning results from diversity based, LD based, and information theoretic algorithms under different values of SNP density and allele frequency. RESULTS: We simulated 1000 haplotypes using the standard coalescent for three world populations--European, African American, and East Asian--and applied three classes of block partitioning algorithms--diversity based, LD based, and information theoretic. We assessed algorithm differences in number, size, and coverage of blocks inferred under different conditions of SNP density, allele frequency, and sample size. Each algorithm inferred blocks differing in number, size, and coverage under different density and allele frequency conditions. Different partitions had few if any matching block boundaries. However they still overlapped and a high percentage of total chromosomal region was common to all methods. This percentage was generally higher with a higher density of SNPs and when rarer markers were included. CONCLUSION: A gold standard definition of a haplotype block is difficult to achieve, but collecting haplotypes covered with a high density of SNPs, partitioning them with a variety of block algorithms, and identifying regions common to all methods may be the best way to identify genomic regions that harbor SNP variants that cause disease.

We describe problems associated with accessing data resources external to the application, which we term externalities, in replicated synchronous collaborative applications. Accessing externalities such as files, databases, network connections, environment variables, and the system clock is not as straightforward in replicated collaborative software as in single-user applications or centralized collaborative systems. We describe ad hoc solutions that add to development cost and complexity because the developer must program different behavior for different replicas. We introduce a novel general approach to accessing externalities uniformly in a replicated collaborative system. The approach uses a semireplicated architecture where the actual externality resides at a single location and is accessed via replicated proxies. This approach allows developers of replicated synchronous groupware to (1) use similar externality access mechanisms as in traditional single-user applications, and (2) program all replicas to execute the same behavior. We describe a general design for proxied access to read-only, write-only, and read-write externalities and discuss the tradeoffs of this semireplicated approach over full, literal replication and the class of applications to which this approach can be successfully applied. We also describe details of a prototype implementation of this approach within a replicated collaboration-transparency system, called Flexible JAMM (Java Applets Made Multiuser).

We present a new deterministic algorithm for constructing endomorphism rings of a finite dimensional module M, given via a vertex projective presentation, over finite dimensional quotients of path algebras. We use the theory of right Gröbner basis to encode M and to construct appropriate systems of equations for finding the endomorphism ring of M. The algorithm is implemented in the computer algebra system GAP and is included in HOPF, a computational package for noncommutative algebra. We compare the performance of our implementation with implementations of existing algorithms for computing endomorphism rings.

People interact together in all aspects of life and, as computers have become prevalent, users seek computer support for their interactions.The WWW provides an unprecedented opportunity for users to interact with each other, and the advent of JavaThfl has created a consistent computing environment to support synchronous collaboration.We describe JAMM, a prototype Java runtime environment that supports the shared use of existing Java applets, thus leveraging the existing base of software for synchronous collaboration.Our approach is based on a replicated architecture, where each user maintains their own copy of the Java applet, and the users' input events are broadcast to each applet copy.We discuss solutions to certain key problems, such as unanticipated sharing, supporting late-joiners, and replicating input sources other than user inputs (e.g., files, sockets, and random number generators).