Cost-Effective Cloud Computing: A Case Study Using the Comparative Genomics Tool, Roundup

Background Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource—Roundup—using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Methods Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon's Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. Results We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon's computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure

A Simulation Platform to Examine Heterogeneity Influence on Treatment

Although a protocol aims to guide treatment management and optimize overall outcomes, the benefits and harms for each individual vary due to heterogeneity. Some protocols integrate clinical and genetic variation to provide treatment recommendation; it is not clear whether such integration is sufficient. If not, treatment outcomes may be sub-optimal for certain patient sub-populations. Unfortunately, running a clinical trial to examine such outcome responses is cost prohibitive and requires a significant amount of time to conduct the study. We propose a simulation approach to discover this knowledge from electronic medical records; a rapid method to reach this goal. We use the well-known drug warfarin as an example to examine whether patient characteristics, including race and the genes CYP2C9 and VKORC1, have been fully integrated into dosing protocols. The two genes mentioned above have been shown to be important in patient response to warfarin

Genotator: A disease-agnostic tool for genetic annotation of disease

<p>Abstract</p> <p>Background</p> <p>Disease-specific genetic information has been increasing at rapid rates as a consequence of recent improvements and massive cost reductions in sequencing technologies. Numerous systems designed to capture and organize this mounting sea of genetic data have emerged, but these resources differ dramatically in their disease coverage and genetic depth. With few exceptions, researchers must manually search a variety of sites to assemble a complete set of genetic evidence for a particular disease of interest, a process that is both time-consuming and error-prone.</p> <p>Methods</p> <p>We designed a real-time aggregation tool that provides both comprehensive coverage and reliable gene-to-disease rankings for any disease. Our tool, called Genotator, automatically integrates data from 11 externally accessible clinical genetics resources and uses these data in a straightforward formula to rank genes in order of disease relevance. We tested the accuracy of coverage of Genotator in three separate diseases for which there exist specialty curated databases, Autism Spectrum Disorder, Parkinson's Disease, and Alzheimer Disease. Genotator is freely available at <url>http://genotator.hms.harvard.edu</url>.</p> <p>Results</p> <p>Genotator demonstrated that most of the 11 selected databases contain unique information about the genetic composition of disease, with 2514 genes found in only one of the 11 databases. These findings confirm that the integration of these databases provides a more complete picture than would be possible from any one database alone. Genotator successfully identified at least 75% of the top ranked genes for all three of our use cases, including a 90% concordance with the top 40 ranked candidates for Alzheimer Disease.</p> <p>Conclusions</p> <p>As a meta-query engine, Genotator provides high coverage of both historical genetic research as well as recent advances in the genetic understanding of specific diseases. As such, Genotator provides a real-time aggregation of ranked data that remains current with the pace of research in the disease fields. Genotator's algorithm appropriately transforms query terms to match the input requirements of each targeted databases and accurately resolves named synonyms to ensure full coverage of the genetic results with official nomenclature. Genotator generates an excel-style output that is consistent across disease queries and readily importable to other applications.</p

Photocatalytic Performance of Undoped and Al-Doped ZnO Nanoparticles in the Degradation of Rhodamine B under UV-Visible Light:The Role of Defects and Morphology

Quasi-spherical undoped ZnO and Al-doped ZnO nanoparticles with different aluminum content, ranging from 0.5 to 5 at% of Al with respect to Zn, were synthesized. These nanoparticles were evaluated as photocatalysts in the photodegradation of the Rhodamine B (RhB) dye aqueous solution under UV-visible light irradiation. The undoped ZnO nanopowder annealed at 400 &deg;C resulted in the highest degradation efficiency of ca. 81% after 4 h under green light irradiation (525 nm), in the presence of 5 mg of catalyst. The samples were characterized using ICP-OES, PXRD, TEM, FT-IR, 27Al-MAS NMR, UV-Vis and steady-state PL. The effect of Al-doping on the phase structure, shape and particle size was also investigated. Additional information arose from the annealed nanomaterials under dynamic N2 at different temperatures (400 and 550 &deg;C). The position of aluminum in the ZnO lattice was identified by means of 27Al-MAS NMR. FT-IR gave further information about the type of tetrahedral sites occupied by aluminum. Photoluminescence showed that the insertion of dopant increases the oxygen vacancies reducing the peroxide-like species responsible for photocatalysis. The annealing temperature helps increase the number of red-emitting centers up to 400 &deg;C, while at 550 &deg;C, the photocatalytic performance drops due to the aggregation tendency

Anticoagulation After Stroke in Patients With Atrial Fibrillation : To Bridge or Not With Low-Molecular-Weight Heparin?

Background and Purpose- Bridging therapy with low-molecular-weight heparin reportedly leads to a worse outcome for acute cardioembolic stroke patients because of a higher incidence of intracerebral bleeding. However, this practice is common in clinical settings. This observational study aimed to compare (1) the clinical profiles of patients receiving and not receiving bridging therapy, (2) overall group outcomes, and (3) outcomes according to the type of anticoagulant prescribed. Methods- We analyzed data of patients from the prospective RAF and RAF-NOACs studies. The primary outcome was defined as the composite of ischemic stroke, transient ischemic attack, systemic embolism, symptomatic cerebral bleeding, and major extracerebral bleeding observed at 90 days after the acute stroke. Results- Of 1810 patients who initiated oral anticoagulant therapy, 371 (20%) underwent bridging therapy with full-dose low-molecular-weight heparin. Older age and the presence of leukoaraiosis were inversely correlated with the use of bridging therapy. Forty-two bridged patients (11.3%) reached the combined outcome versus 72 (5.0%) of the nonbridged patients (P=0.0001). At multivariable analysis, bridging therapy was associated with the composite end point (odds ratio, 2.3; 95% CI, 1.4-3.7; P Conclusions- Our findings suggest that patients receiving low-molecular-weight heparin have a higher risk of early ischemic recurrence and hemorrhagic transformation compared with nonbridged patients.Peer reviewe

New Green Business Model for Sustainable Finance

Emerging markets for environmental financial investment and trading continue to attract significant global investment interest but little investment capital as yet. According to Cleantech Venture Network, $5.18 billion was deployed for clean-tech investment in global markets for 2007. For research and development in the same year, U.S. energy companies committed only$4 billion and the U.S. federal government spent $7.5 billion. It is now estimated that underinvestment in U.S. energy and water infrastructure is over$2 trillion. This underinvestment has been held up by regulatory uncertainty of the United States on federal climate change legislation as well as the lack of attention by politicians. That will now change with the next U.S. administration. As markets change, so do investment models. The new business model that has emerged for investment in alternative energy and clean technology is a hybrid business model of venture capital, hedge funds, and private equity. Investment is locked up for shorter periods of time, from one to four years, rather than with traditional venture capital time spans of up to 10 years. Coupled with the project orientation of the investment, there also is a dimension of credit trading for emissions, carbon, and renewable energy included in this investment strategy. The blurring of the lines among hedge funds, private equity funds, and venture capital is being exacerbated by significant private equity participation in environmental finance. This new hybrid financial green investment model will be discussed and analyzed in this paper

Energy convergence: The beginning of the multi commodity market

Another outstanding contributon to the understanding of risk management by Peter Fusaro