Parallel and scalable combinatorial string algorithms on distributed memory systems

Methods for processing and analyzing DNA and genomic data are built upon combinatorial graph and string algorithms. The advent of high-throughput DNA sequencing is enabling the generation of billions of reads per experiment. Classical and sequential algorithms can no longer deal with these growing data sizes - which for the last 10 years have greatly out-paced advances in processor speeds. Processing and analyzing state-of-the-art genomic data sets require the design of scalable and efficient parallel algorithms and the use of large computing clusters. Suffix arrays and trees are fundamental string data structures, which lie at the foundation of many string algorithms, with important applications in text processing, information retrieval, and computational biology. Conversely, the parallel construction of these indices is an actively studied problem. However, prior approaches lacked good worst-case run-time guarantees and exhibit poor scaling and overall performance. In this work, we present our distributed-memory parallel algorithms for indexing large datasets, including algorithms for the distributed construction of suffix arrays, LCP arrays, and suffix trees. We formulate a generalized version of the All-Nearest-Smaller-Values problem, provide an optimal distributed solution, and apply it to the distributed construction of suffix trees - yielding a work-optimal parallel algorithm. Our algorithms for distributed suffix array and suffix tree construction improve the state-of-the-art by simultaneously improving worst-case run-time bounds and achieving superior practical performance. Next, we introduce a novel distributed string index, the Distributed Enhanced Suffix Array (DESA) - based on the suffix and LCP arrays, the DESA consists of these and additional distributed data structures. The DESA is designed to allow efficient pattern search queries in distributed memory while requiring at most O(n/p) memory per process. We present efficient distributed-memory parallel algorithms for querying, as well as for the efficient construction of this distributed index. Finally, we present our work on distributed-memory algorithms for clustering de Bruijn graphs and its application to solving a grand challenge metagenomic dataset.Ph.D

2004 Research Engineering Annual Report

Selected research and technology activities at Dryden Flight Research Center are summarized. These activities exemplify the Center's varied and productive research efforts

2003 Research Engineering Annual Report

Selected research and technology activities at Dryden Flight Research Center are summarized. These activities exemplify the Center's varied and productive research efforts

Welfare conditionality in lived experience : aggregating qualitative longitudinal research

Punitive welfare conditionality, combining tough sanctions with minimal self-directed support, is a defining feature of contemporary UK working age social security provision. This approach has been justified by policy makers on the basis that it will increase the numbers in paid employment, and thereby offering savings for the public purse that are also beneficial for individuals who are expected to be healthier and better off financially as a result. In this article, we aggregate two qualitative longitudinal studies (Welfare Conditionality, 2014-17; and Lived Experience, 2011-16) that document lived experiences of claiming benefits and using back-to-work support services. In both studies and over time, we find, contrary to policy expectations, that coercion, including sanctions, was usually experienced as unnecessary and harmful and that poverty was prevalent, both in and out of work, tended to worsen and pushed many close to destitution. Conditionality governed encounters with employment services and, perversely, appeared to impede, rather than support, transitions into employment for participants in both studies. In this way, we propose Combined Study Qualitative Longitudinal Research as a new methodological approach for investigating if ‘shared typical’ aspects of lived experiences of welfare conditionality can be identified

High Throughput Functional Assays of the Variant Antigen PfEMP1 Reveal a Single Domain in the 3D7 Plasmodium falciparum Genome that Binds ICAM1 with High Affinity and Is Targeted by Naturally Acquired Neutralizing Antibodies

Plasmodium falciparum–infected erythrocytes bind endothelial receptors to sequester in vascular beds, and binding to ICAM1 has been implicated in cerebral malaria. Binding to ICAM1 may be mediated by the variant surface antigen family PfEMP1: for example, 6 of 21 DBLβC2 domains from the IT4 strain PfEMP1 repertoire were shown to bind ICAM1, and the PfEMP1 containing these 6 domains are all classified as Group B or C type. In this study, we surveyed binding of ICAM1 to 16 DBLβC2 domains of the 3D7 strain PfEMP1 repertoire, using a high throughput Bioplex assay format. Only one DBL2βC2 domain from the Group A PfEMP1 PF11_0521 showed strong specific binding. Among these 16 domains, DBL2βC2PF11_0521 best preserved the residues previously identified as conserved in ICAM1-binding versus non-binding domains. Our analyses further highlighted the potential role of conserved residues within predominantly non-conserved flexible loops in adhesion, and, therefore, as targets for intervention. Our studies also suggest that the structural/functional DBLβC2 domain involved in ICAM1 binding includes about 80 amino acid residues upstream of the previously suggested DBLβC2 domain. DBL2βC2PF11_0521 binding to ICAM1 was inhibited by immune sera from east Africa but not by control US sera. Neutralizing antibodies were uncommon in children but common in immune adults from east Africa. Inhibition of binding was much more efficient than reversal of binding, indicating a strong interaction between DBL2βC2PF11_0521 and ICAM1. Our high throughput approach will significantly accelerate studies of PfEMP1 binding domains and protective antibody responses

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements