Cost data analysis
Rnablast (basic local alignment search tool)blast (stand-alone)e-utilitiesgenbankgenbank: bankitgenbank: sequingenbank: tbl2asngenome workbenchinfluenza virusnucleotide databasepopsetprimer-blastprosplignreference sequence (refseq)refseqgenesequence read archive (sra)spligntrace archiveunigeneall dna & rna resources... Softwareblast (basic local alignment search tool)blast (stand-alone)cn3dconserved domain search service (cd search)e-utilitiesgenbank: bankitgenbank: sequingenbank: tbl2asngenome protmapgenome workbenchprimer-blastprosplignpubchem structure searchsnp submission toolsplignvector alignment search tool (vast)all data & software resources... Structuresbiosystemscn3dconserved domain database (cdd)conserved domain search service (cd search)structure (molecular modeling database)vector alignment search tool (vast)all domains & structures resources... Expressionbiosystemsdatabase of genotypes and phenotypes (dbgap)e-utilitiesgenegene expression omnibus (geo) database gene expression omnibus (geo) datasetsgene expression omnibus (geo) profilesgenome workbenchhomologenemap vieweronline mendelian inheritance in man (omim)refseqgeneunigeneall genes & expression resources... Medicinebookshelfdatabase of genotypes and phenotypes (dbgap)genetic testing registryinfluenza virusmap vieweronline mendelian inheritance in man (omim)pubmedpubmed central (pmc)pubmed clinical queriesrefseqgeneall genetics & medicine resources... Mapsdatabase of genomic structural variation (dbvar)genbank: tbl2asngenomegenome projectgenome protmapgenome workbenchinfluenza virusmap viewernucleotide databasepopsetprosplignsequence read archive (sra)spligntrace archiveall genomes & maps resources... Basic local alignment search tool)blast (stand-alone)blast link (blink)conserved domain database (cdd)conserved domain search service (cd search)genome protmaphomologeneprotein clustersall homology resources... Utilitiesjournals in ncbi databasesmesh databasencbi handbookncbi help manualncbi news & blogpubmedpubmed central (pmc)pubmed clinical queriespubmed healthall literature resources... Basic local alignment search tool)blast (stand-alone)blast link (blink)conserved domain database (cdd)conserved domain search service (cd search)e-utilitiesprosplignprotein clustersprotein databasereference sequence (refseq)all proteins resources... Analysisblast (basic local alignment search tool)blast (stand-alone)blast link (blink)conserved domain search service (cd search)genome protmapgenome workbenchinfluenza virusprimer-blastprosplignsplignall sequence analysis resources... Of genomic structural variation (dbvar)database of genotypes and phenotypes (dbgap)database of single nucleotide polymorphisms (dbsnp)snp submission toolall variation resources... Toall how tochemicals & bioassaysdna & rnadata & softwaredomains & structuresgenes & expressiongenetics & medicinegenomes & mapshomologyliteratureproteinssequence analysistaxonomytraining & tutorialsvariationabout ncbi accesskeysmy ncbisign in to ncbisign : abstractformatsummarysummary (text)abstractabstract (text)medlinexmlpmid listapplysend tochoose destinationfileclipboardcollectionse-mailordermy bibliographycitation managerformatsummary (text)abstract (text)medlinexmlpmid listcsvcreate file1 selected item: 11154790formatsummarysummary (text)abstractabstract (text)medlinexmlpmid listmesh and other datae-mailsubjectadditional texte-maildidn't get the message?
2000 dec;54(3):is and interpretation of cost data in dialysis: review of western european s p1, rublee d, just pm, joseph information1the lewin group, 3-5 rue maurice ravel, 92594 levallois perret, cedex, ctbackground: constant improvements in dialysis technology, combined with a growing chronic renal failure population and limited funds, have put clinicians under pressure to prescribe the most cost-effective therapies. Improvements in dialysis, which eliminates metabolic waste products and preserves a normal electrolyte and fluid balance, have enhanced the quality of care among renal patients but at high monetary cost to health systems. Several recent studies report that yearly costs of peritoneal dialysis (pd) (because of technical differences in treatment strategies) are less than hemodialysis (hd) with hospital and other costs included. Furthermore, input costs, health care organizations, and patient use of dialysis vary from country to country in important ive: to review critically the european literature in dialysis where cost data in caring for patients is available, and maximize information about the nature of the cost data in s: survey of published literature including an economic evaluation with cost values in western europe; 25 such studies were identified, described in 20 publications. The appraisal of studies took place according to standard costing procedures, covering, but not limited to, specification of analytic perspective and cost components s: costs between dialysis modalities vary from country to country in important ways, although power to detect such differences was limited. Only four studies presented adequate descriptive information for dialysis sions: errors should be expected in all exercises to estimate dialysis costs. But, potentially misleading conclusions about the relative costs of dialysis therapies have been published in the absence of supporting evidence. The review suggests a positive cost advantage to peritoneal dialysis over hemodialysis, but the magnitude of the difference is difficult to evaluate at this : 11154790 [indexed for medline] sharepublication types, mesh termspublication typescomparative studyresearch support, non-u. Gov'treviewmesh termscosts and cost analysisdata interpretation, statisticaleuropehealth care costs/statistics & numerical data*health services researchhumansrenal dialysis/economics*renal insufficiency/economicsrenal insufficiency/therapy*linkout - more resourcesfull text sourceselsevier sciencemedicaldialysis - medlineplus health informationpubmed commons home. Commentshow to join pubmed commonshow to cite this comment:Ncbi > literature > the cost analysis reportcompare ad cost and revenue across your paid marketing cost analysis report shows session, cost, and revenue performance data for your paid non-google marketing channels. The report compares the cost of each campaign with its associated revenue (from ecommerce and/or goal value) to calculate roas (return on ad spend) and rpc (revenue per click). These metrics let you quickly see how each initiative the cost analysis about cost the cost analysis in to google te to your acquisition > cost about cost cost analysis report shows metrics for "google/cpc" (adwords) and any other channel for which you upload cost data.
For example, the report will display cost and performance metrics for non-google search engine campaigns and keywords if you upload the associated cost data. Adwords data appears as long as your adwords and analytics accounts are linked, and the adwords cost data has been imported to the view you're looking cost analysis report analyzes costs for your non-google ad campaigns. If you have auto-tagging enabled, adwords cost data will already be available in those reports by how to upload click and cost adwords and e cost data with attribution more about the benefits of this: was this article helpful? Toall how tochemicals & bioassaysdna & rnadata & softwaredomains & structuresgenes & expressiongenetics & medicinegenomes & mapshomologyliteratureproteinssequence analysistaxonomytraining & tutorialsvariationabout ncbi accesskeysmy ncbisign in to ncbisign : abstractformatsummarysummary (text)abstractabstract (text)medlinexmlpmid listapplysend tochoose destinationfileclipboardcollectionse-mailordermy bibliographycitation managerformatsummary (text)abstract (text)medlinexmlpmid listcsvcreate file1 selected item: 19358578formatsummarysummary (text)abstractabstract (text)medlinexmlpmid listmesh and other datae-mailsubjectadditional texte-maildidn't get the message? Cost, scalable proteomics data analysis using amazon's cloud computing services and open source search an bd1, geiger jf, vallejos ak, greene as, twigger information1biotechnology and bioengineering center, medical college of wisconsin, 8701 watertown plank road, milwaukee, wisconsin 53226, usa. Halligan@tractone of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as amazon web services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step-by-step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured amazon machine images containing the omssa and x! Search algorithms and sequence databases on the medical college of wisconsin proteomics center web site ( http:///vipdac ). Pr800970z [indexed for medline] free pmc articleshareimages from this all images (3)free textfigure 1flowchart of vipdac workflowlow cost, scalable proteomics data analysis using amazon's cloud computing services and open source search algorithmsj proteome res. 8(6): 2uml case study diagram for vipdaclow cost, scalable proteomics data analysis using amazon's cloud computing services and open source search algorithmsj proteome res.
8(6): 3time and cost of different vidac configurationswall clock time to complete the analysis is indicated in filled diamonds and solid lines. Costs are in us dollars as of 11/1/ cost, scalable proteomics data analysis using amazon's cloud computing services and open source search algorithmsj proteome res. Extramuralmesh termsalgorithms*cluster analysisdatabases, proteininternetproteomics/methods*software*grant supportn01 hv028182/hl/nhlbi nih hhs/united statesn01 hv-28182/hv/nhlbi nih hhs/united stateslinkout - more resourcesfull text sourcesamerican chemical societyeurope pubmed central - author manuscriptpubmed central - author manuscriptpubmed central canada - author manuscriptother literature sourcescos scholar universecited by patents in - the lenspubmed commons home. Ponemon cost of data breach ® is proud to sponsor the 12th annual cost of data breach study, the industry’s gold-standard benchmark research, independently conducted by ponemon institute. This year’s study reports the global average cost of a data breach is down 10 percent over previous years to $3. The average cost for each lost or stolen record containing sensitive and confidential information also significantly decreased from $158 in 2016 to $141 in this year’s r, despite the decline in the overall cost, companies in this year’s study are having larger breaches. Country-specific of data breach ies face the constant, rising threat of data breaches each year. This interactive experience can help the ad cost of data breach about the global impact of a data er to download the y-specific er how a data breach affects selected of business continuity management how business continuity management can reduce the cost and impact of a data er to download the report. Ibm can er how you can prevent future data a secure enterprise with increased er more x-force threat intelligence the 2017 report. Cost of data breach e highlights from ponemon's global ibm's ransomware client the infographic (pdf, 219kb). Ibmsecurity on ibmsecurity on sequencing costs: search term(s):Division of genome sciences -scale genome sequencing and analysis centers (lsac). Many years, the national human genome research institute (nhgri) has tracked the costs associated with dna sequencing performed at the sequencing centers funded by the institute.
Here, nhgri provides an analysis of these data, which gives one view of the remarkable improvements in dna sequencing technologies and data-production pipelines in recent cost-accounting data presented here are summarized relative to two metrics: (1) "cost per megabase of dna sequence" - the cost of determining one megabase (mb; a million bases) of dna sequence of a specified quality [see below]; (2) "cost per genome" - the cost of sequencing a human-sized genome. For each, a graph is provided showing the data since 2001; in addition, the actual numbers reflected by the graphs are provided in a summary table. View the data in sequencing costs both graphs, note: (1) the use a logarithmic scale on the y axis; and (2) the sudden and profound out-pacing of moore's law beginning in january 2008. Additional details about these graphs are provided data, however, do not capture all of the costs associated with the nhgri large-scale genome sequencing program. The sequencing centers perform a number of additional activities whose costs are not appropriate to include when calculating costs for production-oriented dna sequencing. Production activities are essential to the routine generation of large amounts of quality dna sequence data that are made available in public databases; the costs associated with production dna sequencing are summarized here and depicted on the two graphs. Additional information about the other activities performed by the sequencing centers is provided expenditures included in each category were established based on discussions between nhgri staff and sequencing center the two graphs ("cost per megabase of dna sequence" and "cost per genome"), the following 'production' costs are accounted for:Labor, administration, management, utilities, reagents, and cing instruments and other large equipment (amortized over three years). Of data to a public ct costs (http:///dfas/faq/indirect-costs#difference) as they relate to the above the case of costs covered by significant subsidies to a sequencing center (e. A grantee institution providing funds for purchasing large equipment), nhgri has attempted to appropriately account for such costs in these costs associated with the following 'non-production' activities are not reflected in the two graphs:Quality assessment/control for sequencing logy development to improve sequencing pment of bioinformatics/computational tools to improve sequencing pipelines or to improve downstream sequence ment of individual sequencing atics analysis downstream of initial data processing (e. Sequencing both graphs, the data from 2001 through october 2007 represent the costs of generating dna sequence using sanger-based chemistries and capillary-based instruments ('first generation' sequencing platforms). Beginning in january 2008, the data represent the costs of generating dna sequence using 'second-generation' (or 'next-generation') sequencing platforms. The change in instruments represents the rapid evolution of dna sequencing technologies that has occurred in recent the sanger-based sequence data, the cost accounting reflects the generation of bases with a minimum quality score of phred20 (or q20), which represents an error probability of 1 % and is an accepted community standard for a high-quality base.
For sequence data generated with second-generation sequencing platforms, there is not yet a single accepted measure of accuracy; each manufacturer provides quality scores that are, at this time, accepted by the nhgri sequencing centers as equivalent to or greater than the "cost per megabase of dna sequence" graph, the data reflect the cost of generating raw, unassembled sequence data; no adjustment was made for data generated using different instruments despite significant differences in the sequence read lengths. In contrast, the "cost per genome" graph does take these differences into account since sequence read length influences the ability to generate an assembled genome "cost per genome" graph was generated using the same underlying data as that used to generate the "cost per megabase of dna sequence" graph; the former thus reflects an estimate of the cost of sequencing a human-sized genome rather than the actual costs for specific genome-sequencing calculate the cost for sequencing a genome, one needs to know the size of that genome and the required 'sequence coverage' (i. The assumed sequence coverage needed differed among sequencing platforms, depending on the average sequence read length for that following 'sequence coverage' values were used in calculating the cost per genome:Sanger-based sequencing (average read length=500-600 bases): 6-fold coverage. Sequencing (average read length=300-400 bases): 10-fold na and solid sequencing (average read length=75-150 bases): 30-fold data since january 2008 (representing data generated using 'second-generation' sequencing platforms), the "cost per genome" graph reflects projects involving the 're-sequencing' of the human genome, where an available reference human genome sequence is available to serve as a backbone for downstream data analyses.