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Results for “Performance benchmarking”

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PubMed1996

Studies on nutrient requirements and cost-effective supplements for ethanol production by recombinant E. coli.

This article describes a systematic study of the nutritional requirements of a patented recombinant ethanologenic Escherichia coli (11303:pLO1297) and provides cost-effective formulations that are compatible with the production of fuel ethanol in fermentations of lignocellulosic prehydrolysate characterized by high xylose conversion efficiency. A complex and nutrient-rich laboratory medium, Luria broth (LB), provided the benchmark with respect to fermentation performance standard. Xylose fermentation performance was assessed in terms of the target values for operational process parameters established by the US National Renewable Energy Laboratory (NREL)-final ethanol concentration (25 g/L), xylose-to-ethanol conversion efficiency (90%), and volumetric productivity (0.52 g/L.h). Biomass prehydrolysates that are rich in xylose also contain acetic acid, and in anticipation of a need to reduce acetic acid toxicity, the fermentors were operated with a pH control set-point of 7.0 Growth and fermentation in the minimal defined salts (DS) medium was only about 15% compared to the reference medium. Amendment of the minimal medium containing 6 wt% xylose with both vitamins and amino acids resulted in improved growth, but the volume productivity (0.59 g/L.h) was still only about 54% of that with LB (1.1g/L.h). Formulations directed at cost reduction through the use of less expensive commercial complex nutritional supplements were within 90% of the NREL process target with respect to yield and provided a productivity at about 80% of the LB medium, but were not economical. Corn steep liquor (CSL) at about 7-8 g/L was shown to be a complete source of nutritional requirements and supported a fermentation performance approaching that of LB. At a cost of CSL of $50/t(dry wt), the economic impact of using this amount CSL as the sole nutritional supplement in a cellulosic ethanol plant was estimated to be about 4 cents/gal of ethanol.

Chimera↗

PubMed2006

Pivoting approaches for bulk extraction of Entity-Attribute-Value data.

Entity-Attribute-Value (EAV) data, as present in repositories of clinical patient data, must be transformed (pivoted) into one-column-per-parameter format before it can be used by a variety of analytical programs. Pivoting approaches have not been described in depth in the literature, and existing descriptions are dated. We describe and benchmark three alternative algorithms to perform pivoting of clinical data in the context of a clinical study data management system. We conclude that when the number of attributes to be returned is not too large, it is feasible to use static SQL as the basis for views on the data. An alternative but more complex approach that utilizes hash tables and the presence of abundant random-access-memory can achieve improved performance by reducing the load on the database server.

Algorithms↗

PubMed2024

Combining Data Independent Acquisition With Spike-In SILAC (DIA-SiS) Improves Proteome Coverage and Quantification.

Data-independent acquisition (DIA) is increasingly preferred over data-dependent acquisition due to its higher throughput and fewer missing values. Whereas data-dependent acquisition often uses stable isotope labeling to improve quantification, DIA mostly relies on label-free approaches. Efforts to integrate DIA with isotope labeling include chemical methods like mass differential tags for relative and absolute quantification and dimethyl labeling, which, while effective, complicate sample preparation. Stable isotope labeling by amino acids in cell culture (SILAC) achieves high labeling efficiency through the metabolic incorporation of heavy labels into proteins in vivo. However, the need for metabolic incorporation limits the direct use in clinical scenarios and certain high-throughput experiments. Spike-in SILAC (SiS) methods use an externally generated heavy sample as an internal reference, enabling SILAC-based quantification even for samples that cannot be directly labeled. Here, we combine DIA-SiS, leveraging the robust quantification of SILAC without the complexities associated with chemical labeling. We developed DIA-SiS and rigorously assessed its performance with mixed-species benchmark samples on bulk and single cell-like amount level. We demonstrate that DIA-SiS substantially improves proteome coverage and quantification compared to label-free approaches and reduces incorrectly quantified proteins. Additionally, DIA-SiS proves effective in analyzing proteins in low-input formalin-fixed paraffin-embedded tissue sections. DIA-SiS combines the precision of stable isotope-based quantification with the simplicity of label-free sample preparation, facilitating simple, accurate, and comprehensive proteome profiling.

Isotope Labeling↗

PubMed2004

Multicriteria decision approaches to support sustainable drainage options for the treatment of highway and urban runoff.

The control and treatment of urban and highway runoff involves a variety of stakeholders in the selection of sustainable drainage systems (SUDS) as the design process needs to consider not only water quantity but also water quality and amenity. Thus, technical, environmental/ecological, social/community and economic cost factors become prime potential sustainability criteria in terms of assessing long-term, cost-effective drainage options. The paper develops a multicriteria analysis methodology for the evaluation and accreditation of SUDS structures within the context of an overall decision-support framework. Approaches independently developed in the UK and France are outlined with the common multicriteria structures defining generic performance criteria together with supporting benchmark standards and exclusion thresholds. A French case study is presented to illustrate the approach and to highlight the inherent constraints and subjectivity embedded in the decision-making process.

Benchmarking↗

PubMed2000

Using prospective outcomes data to improve morbidity and mortality conferences.

Background:Though a traditional part of most training programs, surgical morbidity and mortality (M&M) conferences are not optimal for teaching residents how to understand and improve patient outcomes. They tend to focus on unusual rather than common problems and review complications as singular phenomena, rather than recurrent events related to specific processes of care. For these reasons, we began incorporating data from our general surgery outcomes registry into our M&M conference.Developed for both clinical research and quality improvement purposes, the outcomes registry contains prospective information about all patients undergoing general surgery procedures in the operating room (approximately 2000 per year). All adverse events occurring within 30 days of surgery are categorized, using explicit criteria, by clinical nurse coordinators. Individual complications are then collapsed into four severity grades (from a previously validated grading system), from I (not life-threatening, low complexity therapy; eg, superficial wound infection) to IV (death).Application To M&M Conferences:Before each conference the data manager supplies the responsible senior resident with information about caseloads and adverse events for the preceding month. At the conference, individual cases are presented in the context of the department's broader experience with that procedure (eg, rates of wound complications after bowel surgery over the last 2 years). In reviewing trends in complication rates over time, we also explore potential relationships between practice changes and outcomes. When appropriate, local performance is compared to external "benchmarks" using data from published studies.Incorporating prospective outcome data into the M&M conference is both feasible and practical. In addition to its educational value for both resident and attending physicians, we believe this approach creates many opportunities for improving the quality of our surgical practice.

Journal Article↗

PubMed2001

Efficient evaluation of serial sections by iterative Gabor matching.

Evaluation of electron microscopic images of serial sections is a time-consuming process requiring a high level of expertise. Here we present an algorithm to ease and accelerate this process. It is a modification of an algorithm successfully used in computer vision for object recognition. However, rather than recognising individual structures, we estimate the spatial mapping of a whole section onto the consecutive one. This mapping is used to transfer labelled information of the very first section, e.g. a classification by a human expert of different visible structures, onto structures visible in the next section. We investigate its performance on an artificially constructed benchmark as well as on real electron microscopic samples taken in primary visual cortex and demonstrate its potential for dramatically facilitating the evaluation process of serial sections.

Algorithms↗

PubMedDate not supplied

A generalized feedforward neural network architecture for classification and regression.

This article presents a new generalized feedforward neural network (GFNN) architecture for pattern classification and regression. The GFNN architecture uses as the basic computing unit a generalized shunting neuron (GSN) model, which includes as special cases the perceptron and the shunting inhibitory neuron. GSNs are capable of forming complex, nonlinear decision boundaries. This allows the GFNN architecture to easily learn some complex pattern classification problems. In this article the GFNNs are applied to several benchmark classification problems, and their performance is compared to the performances of SIANNs and multilayer perceptrons. Experimental results show that a single GSN can outperform both the SIANN and MLP networks.

Classification↗

PubMed2002

A linkage tournament: affection status, parametric analysis, multivariate traits, and enhancements to variance components and relative pairs.

Linkage tests to localize oligogenes have been extended during the past year. Using simulated data and multiplex selection we find that several tests on affected sib pairs have comparable power and type I error. Three variants of SIBPAL2 are favoured when substantial numbers of normal sibs are included, but performance relative to the BETA benchmark degrades rapidly as normal sibs are depleted by selective sampling or typing. Neglect of this fact may explain recent failure of retrospective collaboration to confirm asthma candidates in the 5q cytokine region that are supported by other studies. A fully quantitative trait favours variance components under complete ascertainment and two options in SIBPAL2 under multiplex selection, with substantial gain in power from covariance analysis if the covariate is independent of the candidate locus. A dichotomy and liability threshold give virtually identical results in the SOLAR variance components program. Comparison with single-marker parametric analysis suggests that extension to multiple markers would be competitive with nonparametric methods in power, and superior in depth of genetic analysis. The simulated examples illustrate common problems encountered with linkage scans for oligogenes. They show that nonparametric methods provide no panacea for analytical problems posed by different phenotypes and methods of ascertainment.

Asthma↗

PubMed2003

Taking a public health approach to the prevention of end-stage renal disease: the NKF Singapore Program.

The National Kidney Foundation Singapore (NKFS) provides subsidized dialysis care to approximately 70% of the country's total end-stage renal disease (ESRD) population, based entirely on charitable donations. Because of the exponential increase in prevalent dialysis patients receiving care through the NKFS' chronic dialysis program, and with the anticipated epidemic rise in incident ESRD patients, an accelerated comprehensive strategy for the prevention of renal and its associated chronic diseases was developed. Presented is the NKFS' public health plan, which incorporates primary, secondary and tertiary approaches to the prevention of chronic kidney disease. Components of this comprehensive strategy include: screening populations at risk for the development and progression of renal disease, the documentation of existing standards of care for chronic diseases associated with renal disease, and the institution of disease management programs that facilitate the systematic management of patients with chronic diseases that lead to ESRD, including the development of community-based "Prevention Centers." Finally, longitudinal follow-up of the participating population is being performed in order to provide benchmarks for improvement and to determine future directions of the program. Such long-term monitoring also will facilitate the establishment of its efficacy in improving clinical outcomes, reducing the cost of care, and delaying the development and progression of chronic kidney disease.

Community Health Services↗

PubMed2005

Effective function annotation through catalytic residue conservation.

Because of the extreme impact of genome sequencing projects, protein sequences without accompanying experimental data now dominate public databases. Homology searches, by providing an opportunity to transfer functional information between related proteins, have become the de facto way to address this. Although a single, well annotated, close relationship will often facilitate sufficient annotation, this situation is not always the case, particularly if mutations are present in important functional residues. When only distant relationships are available, the transfer of function information is more tenuous, and the likelihood of encountering several well annotated proteins with different functions is increased. The consequence for a researcher is a range of candidate functions with little way of knowing which, if any, are correct. Here, we address the problem directly by introducing a computational approach to accurately identify and segregate related proteins into those with a functional similarity and those where function differs. This approach should find a wide range of applications, including the interpretation of genomics/proteomics data and the prioritization of targets for high-throughput structure determination. The method is generic, but here we concentrate on enzymes and apply high-quality catalytic site data. In addition to providing a series of comprehensive benchmarks to show the overall performance of our approach, we illustrate its utility with specific examples that include the correct identification of haptoglobin as a nonenzymatic relative of trypsin, discrimination of acid-d-amino acid ligases from a much larger ligase pool, and the successful annotation of BioH, a structural genomics target.

Amino Acid Sequence↗

PubMed1998

Quantitative biomechanical analysis of wrist motion in bone-trimming jobs in the meat packing industry.

This study was motivated by the serious impact that cumulative trauma disorders (CTDs) of the upper extremities have on the meat packing industry. To date, no quantitative data have been gathered on the kinematics of hand and wrist motion required in bone-trimming jobs in the red-meat packing industry and how these motions are related to the risk of CTDs. The wrist motion of bone-trimming workers from a medium-sized plant was measured, and the kinematic data were compared to manufacturing industry's preliminary wrist motion benchmarks from industrial workers who performed hand-intensive, repetitive work in jobs that were of low and high risk of hand/wrist CTDs. Results of this comparison show that numerous wrist motion variables in both the left and right hands of bone-trimming workers are in the high-risk category. This quantitative analysis provides biomechanical support for the high incidence of CTDs in the meat packing industry. The research reported in this paper established a preliminary database of wrist and hand kinematics required in bone-trimming jobs in the red-meat packing industry. This kinematic database could augment the industry's efforts to reduce the severity and cost of CTDs. Ergonomics practitioners in the industry could use the kinematic methods employed in this research to assess the CTD risk of jobs that require repetitious, hand-intensive work.

Biomechanical Phenomena↗

PubMed2005

Accurate anchoring alignment of divergent sequences.

MOTIVATION: Obtaining high quality alignments of divergent homologous sequences for cross-species sequence comparison remains a challenge. RESULTS: We propose a novel pairwise sequence alignment algorithm, ACANA (ACcurate ANchoring Alignment), for aligning biological sequences at both local and global levels. Like many fast heuristic methods, ACANA uses an anchoring strategy. However, unlike others, ACANA uses a Smith-Waterman-like dynamic programming algorithm to recursively identify near-optimal regions as anchors for a global alignment. Performance evaluations using a simulated benchmark dataset and real promoter sequences suggest that ACANA is accurate and consistent, especially for divergent sequences. Specifically, we use a simulated benchmark dataset to show that ACANA has the highest sensitivity to align constrained functional sites compared to BLASTZ, CHAOS and DIALIGN for local alignment and compared to AVID, ClustalW, DIALIGN and LAGAN for global alignment. Applied to 6007 pairs of human-mouse orthologous promoter sequences, ACANA identified the largest number of conserved regions (defined as over 70% identity over 100 bp) compared to AVID, ClustalW, DIALIGN and LAGAN. In addition, the average length of conserved region identified by ACANA was the longest. Thus, we suggest that ACANA is a useful tool for identifying functional elements in cross-species sequence analysis, such as predicting transcription factor binding sites in non-coding DNA. AVAILABILITY: ACANA software and test sequence data are publicly available at http://BioMedEmpire.org/

Algorithms↗

PubMed2002

Ambulatory antimicrobial use: the value of an outcomes registry.

The opportunity for treating many serious infections in the community or ambulatory setting is growing. Outpatient parenteral antimicrobial therapy (OPAT) provides many potential advantages to the patient, hospital and clinician, including quality of life, cost savings and reduced risk of hospital-acquired infections due to antibiotic-resistant organisms. However, despite the evolution of this type of care in many countries, there have been continued questions and concerns about its safety and effectiveness. As with many new forms of therapy in medicine, the value of OPAT is in doubt because of the lack of published information concerning outcomes and its impact on patient care. In order to examine the quality of such programmes, an outcome-based registry of patients has been developed for OPAT. The core outcomes measures include clinical effectiveness, eradication of bacteria and adverse antibiotic events. The registry may also be adapted for benchmarking for quality assurance, surveying performance of new antimicrobials, cost effectiveness studies and comparisons of different antibiotics and their side effects.

Ambulatory Care↗

PubMed2001

A new tool for benchmarking cardiovascular fluoroscopes.

This paper reports the status of a new cardiovascular fluoroscopy benchmarking phantom. A joint working group of the Society for Cardiac Angiography and Interventions (SCAI) and the National Electrical Manufacturers Association (NEMA) developed the phantom. The device has been adopted as NEMA standard XR 21-2000, 'Characteristics of and Test Procedures for a Phantom to Benchmark Cardiac Fluoroscopic and Photographic Performance' in August 2000. The test ensemble includes imaging-field geometry, spatial resolution, low-contrast iodine detectability, working thickness range, motion unsharpness, and phantom entrance dose. The phantom tests systems under conditions simulating normal clinical use for fluoroscopically guided invasive and interventional procedures. Test procedures rely on trained human observers.

Cardiovascular Diseases↗

PubMed2005

ProbCons: Probabilistic consistency-based multiple sequence alignment.

To study gene evolution across a wide range of organisms, biologists need accurate tools for multiple sequence alignment of protein families. Obtaining accurate alignments, however, is a difficult computational problem because of not only the high computational cost but also the lack of proper objective functions for measuring alignment quality. In this paper, we introduce probabilistic consistency, a novel scoring function for multiple sequence comparisons. We present ProbCons, a practical tool for progressive protein multiple sequence alignment based on probabilistic consistency, and evaluate its performance on several standard alignment benchmark data sets. On the BAliBASE, SABmark, and PREFAB benchmark alignment databases, ProbCons achieves statistically significant improvement over other leading methods while maintaining practical speed. ProbCons is publicly available as a Web resource.

Algorithms↗

PubMedDate not supplied

Fold recognition by predicted alignment accuracy.

One of the key components in protein structure prediction by protein threading technique is to choose the best overall template for a given target sequence after all the optimal sequence-template alignments are generated. The chosen template should have the best alignment with the target sequence since the three-dimensional structure of the target sequence is built on the sequence-template alignment. The traditional method for template selection is called Z-score, which uses a statistical test to rank all the sequence-template alignments and then chooses the first-ranked template for the sequence. However, the calculation of Z-score is time-consuming and not suitable for genome-scale structure prediction. Z-scores are also hard to interpret when the threading scoring function is the weighted sum of several energy items of different physical meanings. This paper presents a Support Vector Machine (SVM) regression approach to directly predict the alignment accuracy of a sequence-template alignment, which is used to rank all the templates for a specific target sequence. Experimental results on a large-scale benchmark demonstrate that SVM regression performs much better than the composition-corrected Z-score method. SVM regression also runs much faster than the Z-score method.

Algorithms↗

PubMed2006

Unsupervised multiscale color image segmentation based on MDL principle.

We present an unsupervised multiscale color image segmentation algorithm. The basic idea is to apply mean shift clustering to obtain an over-segmentation and then merge regions at multiple scales to minimize the minimum description length criterion. The performance on the Berkeley segmentation benchmark campares favorably with some existing approaches.

Algorithms↗

PubMed2004

The generalized LASSO.

In the last few years, the support vector machine (SVM) method has motivated new interest in kernel regression techniques. Although the SVM has been shown to exhibit excellent generalization properties in many experiments, it suffers from several drawbacks, both of a theoretical and a technical nature: the absence of probabilistic outputs, the restriction to Mercer kernels, and the steep growth of the number of support vectors with increasing size of the training set. In this paper, we present a different class of kernel regressors that effectively overcome the above problems. We call this approach generalized LASSO regression. It has a clear probabilistic interpretation, can handle learning sets that are corrupted by outliers, produces extremely sparse solutions, and is capable of dealing with large-scale problems. For regression functionals which can be modeled as iteratively reweighted least-squares (IRLS) problems, we present a highly efficient algorithm with guaranteed global convergence. This defies a unique framework for sparse regression models in the very rich class of IRLS models, including various types of robust regression models and logistic regression. Performance studies for many standard benchmark datasets effectively demonstrate the advantages of this model over related approaches.

Algorithms↗