13526098
Systematic Derivation of Tree Contraction Algorithms
While tree contraction algorithms play an important role in efficient tree computation in parallel, it is difficult to develop such algorithms due to the strict conditions imposed on contracting op...
12853199
Parallelization with Tree Skeletons
Trees are useful data structures, but to design efficient parallel programs over trees is known to be more difficult than to do over lists. Although several important tree skeletons have been proposed to simplify parallel programming on trees, few studies have been reported on how to systematically use them in solving practical problems; it is neither clear how to make a good combination of skeletons to solve a given problem, nor obvious even how to find suitable operators used in a single skeleton. In this paper, we report our first attempt to resolve these problems, proposing two important transformations, the tree diffusion transformation and the tree context preservation transformation. The tree diffusion transformation allows one to use familiar recursive definitions to develop his parallel programs, while the tree context preservation transformation shows how to derive associative operators that are required when using tree skeletons. We illustrate our approach by deriving an efficient parallel program for solving a nontrivial problem called the party planning problem, the tree version of the famous maximum-weight-sum problem.
15997088
A New Parallel Skeleton for General Accumulative Computations
Skeletal parallel programming enables programmers to build a parallel program from ready-made components (parallel primitives) for which efficient implementations are known to exist, making both the parallel program development and the parallelization process easier. Constructing efficient parallel programs is often difficult, however, due to difficulties in selecting a proper combination of parallel primitives and in implementing this combination without having unnecessary creations and exchanges of data among parallel primitives and processors. To overcome these difficulties, we propose a powerful and general parallel skeleton, accumulate, which can be used to naturally code efficient solutions to problems as well as be efficiently implemented in parallel using Message Passing Interface (MPI).
10262758
Deriving structural hylomorphisms from recursive definitions
In functional programming, small programs are often glued together to construct a complex program. Program fusion is an optimizing process whereby these small programs are fused into a single one and intermediate data structures are removed. Recent work has made it clear that this process is especially successful if the recursive definitions are expressed in terms of hylomorphisms. In this paper, we propose an algorithm which can automatically turn all practical recursive definitions into structural hylomorphisms making program fusion be easily applied.
17504195
Parallel skeletons for manipulating general trees
Trees are important datatypes that are often used in representing structured data such as XML. Though trees are widely used in sequential programming, it is hard to write efficient parallel programs manipulating trees, because of their irregular and ill-balanced structures. In this paper, we propose a solution based on the skeletal approach. We formalize a set of skeletons (abstracted computational patterns) for rose trees (general trees of arbitrary shapes) based on the theory of Constructive Algorithmics. Our skeletons for rose trees are extensions of those proposed for lists and binary trees. We show that we can implement the skeletons efficiently in parallel, by combining the parallel binary-tree skeletons for which efficient parallel implementations are already known. As far as we are aware, we are the first who have formalized and implemented a set of simple but expressive parallel skeletons for rose trees.
21046907
Construction of List Homomorphisms by Tupling and Fusion
List homomorphisms are functions which can be efficiently computed in parallel since they ideally suit the divide- sand-conquer paradigm. However, some interesting functions, e.g., the maximum segment sum problem, are not list homomorphisms. In this paper, we propose a systematic way of embedding them into list homomorphisms so that parallel programs are derived. We show, with an example, how a simple, and “obviously” correct, but possibly inefficient solution to the problem can be successfully turned into a semantically equivalent almost homomorphism by means of two transformations: tupling and fusion.
190172
REDfly: a Regulatory Element Database for Drosophila
Bioinformatics studies of transcriptional regulation in the metazoa are significantly hindered by the absence of readily available data on large numbers of transcriptional cis-regulatory modules (CRMs). Even the richly annotated Drosophila melanogaster genome lacks extensive CRM information. We therefore present here a database of Drosophila CRMs curated from the literature complete with both DNA sequence and a searchable description of the gene expression pattern regulated by each CRM. This resource should greatly facilitate the development of computational approaches to CRM discovery as well as bioinformatics analyses of regulatory sequence properties and evolution.
10305231
The Protein Information Resource: an integrated public resource of functional annotation of proteins
The Protein Information Resource (PIR) serves as an integrated public resource of functional annotation of protein data to support genomic/proteomic research and scientific discovery. The PIR, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the PIR-International Protein Sequence Database (PSD), the major annotated protein sequence database in the public domain, containing about 250 000 proteins. To improve protein annotation and the coverage of experimentally validated data, a bibliography submission system is developed for scientists to submit, categorize and retrieve literature information. Comprehensive protein information is available from iProClass, which includes family classification at the superfamily, domain and motif levels, structural and functional features of proteins, as well as cross-references to over 40 biological databases. To provide timely and comprehensive protein data with source attribution, we have introduced a non-redundant reference protein database, PIR-NREF. The database consists of about 800 000 proteins collected from PIR-PSD, SWISS-PROT, TrEMBL, GenPept, RefSeq and PDB, with composite protein names and literature data. To promote database interoperability, we provide XML data distribution and open database schema, and adopt common ontologies. The PIR web site (http://pir.georgetown.edu/) features data mining and sequence analysis tools for information retrieval and functional identification of proteins based on both sequence and annotation information. The PIR databases and other files are also available by FTP (ftp://nbrfa.georgetown.edu/pir_databases).
205878836
A generalization of fan's condition and forbidden subgraph conditions for hamiltonicity
Abstract Let G be a 2-connected graph with n vertices and H be an induced subgraph of G. Denote V0 ≔ {v ϵ V(G): d(v) ⩾ n/2}. If there exists a pair of vertices x and y at distance 2 in H such that {x, y} ⊆ V(H)βV0, then H is called degree light. Let F be the unique graph with degree sequence (1, 1, 1, 3, 3, 3). In this paper, we prove that if G contains no degree light K1, 3 and every degree light F of G contains no induced P4 of G − V0, then G is hamiltonian.
12036966
Literature mining and database annotation of protein phosphorylation using a rule-based system
MOTIVATION
A large volume of experimental data on protein phosphorylation is buried in the fast-growing PubMed literature. While of great value, such information is limited in databases owing to the laborious process of literature-based curation. Computational literature mining holds promise to facilitate database curation.


RESULTS
A rule-based system, RLIMS-P (Rule-based LIterature Mining System for Protein Phosphorylation), was used to extract protein phosphorylation information from MEDLINE abstracts. An annotation-tagged literature corpus developed at PIR was used to evaluate the system for finding phosphorylation papers and extracting phosphorylation objects (kinases, substrates and sites) from abstracts. RLIMS-P achieved a precision and recall of 91.4 and 96.4% for paper retrieval, and of 97.9 and 88.0% for extraction of substrates and sites. Coupling the high recall for paper retrieval and high precision for information extraction, RLIMS-P facilitates literature mining and database annotation of protein phosphorylation.
18834097
Utilization of two sample t-test statistics from redundant probe sets to evaluate different probe set algorithms in GeneChip studies
BackgroundThe choice of probe set algorithms for expression summary in a GeneChip study has a great impact on subsequent gene expression data analysis. Spiked-in cRNAs with known concentration are often used to assess the relative performance of probe set algorithms. Given the fact that the spiked-in cRNAs do not represent endogenously expressed genes in experiments, it becomes increasingly important to have methods to study whether a particular probe set algorithm is more appropriate for a specific dataset, without using such external reference data.ResultsWe propose the use of the probe set redundancy feature for evaluating the performance of probe set algorithms, and have presented three approaches for analyzing data variance and result bias using two sample t-test statistics from redundant probe sets. These approaches are as follows: 1) analyzing redundant probe set variance based on t-statistic rank order, 2) computing correlation of t-statistics between redundant probe sets, and 3) analyzing the co-occurrence of replicate redundant probe sets representing differentially expressed genes. We applied these approaches to expression summary data generated from three datasets utilizing individual probe set algorithms of MAS5.0, dChip, or RMA. We also utilized combinations of options from the three probe set algorithms. We found that results from the three approaches were similar within each individual expression summary dataset, and were also in good agreement with previously reported findings by others. We also demonstrate the validity of our findings by independent experimental methods.ConclusionAll three proposed approaches allowed us to assess the performance of probe set algorithms using the probe set redundancy feature. The analyses of redundant probe set variance based on t-statistic rank order and correlation of t-statistics between redundant probe sets provide useful tools for data variance analysis, and the co-occurrence of replicate redundant probe sets representing differentially expressed genes allows estimation of result bias. The results also suggest that individual probe set algorithms have dataset-specific performance.