Predictive algorithms and T cell epitope mapping.
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Algorithms↗
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Evaluation of the P-POSSUM mortality prediction algorithm in Australian surgical intensive care unit patients.
BACKGROUND: The Physiological and Operative Severity Score for enUmeration of Mortality and Morbidity (POSSUM) is an auditing tool designed to compare surgical outcomes independent of case mix. It uses patient physiological and operative data to predict morbidity and mortality for surgical patients. Thus far most evaluations of the POSSUM algorithm and its modifications have emanated from British hospitals. A single-centre retrospective study was therefore performed to determine the applicability of this tool to the Australian surgical case mix. METHODS: All surgical patients undergoing a surgical procedure admitted to the Royal Brisbane Hospital intensive care facility in 1999 were reviewed retrospectively. Mortality predictions using the Portsmouth modification of the POSSUM algorithm (P--POSSUM) were compared to the actual outcomes using receiver-operator characteristic curve analysis and the Hosmer and Lemeshow Goodness-of-Fit test. RESULTS: The records of 229 admissions were reviewed. The area under the receiver-operator characteristic curve was 0.68, significantly greater than 0.5 (P = 0.014). Predicted deaths were significantly greater than actual deaths (50 vs 28, P < 0.001), with over-prediction of death rates in all mortality groupings except the two lowest risk deciles. CONCLUSION: The P-POSSUM algorithm tends to over-estimate mortality in surgical intensive care patients. It may require further calibration before adoption as a surgical audit tool in Australia.
Aged↗
Pre-endoscopic prognostic factors in non-varicose upper gastrointestinal bleeding. Development of a predictive algorithm.
OBJECTIVE: Upper gastrointestinal or digestive bleeding (UDB) is a common problem requiring hospitalization and implying important morbidity-mortality. The aim of the present study is to identify clinical and laboratory factors predictive of a serious course of non-varicose UDB, based on the development of a simple algorithm for application in the clinical setting. METHODS: A longitudinal study was made of 803 hospitalized patients with non-varicose UDB. Clinical and laboratory parameters were recorded in the Emergency Service before endoscopy. A first non-conditional logistic regression model was developed, including those variables exhibiting a greater capacity for predicting a serious outcome. This model was posteriorly simplified to facilitate clinical application. The prognostic performance was estimated by calculating the area under the ROC curve. RESULTS: The initial predictive model included 11 variables, with an area under the ROC curve of 0.74 (95%CI: 0.71-0.77), while in the second model these same variables were dichotomized, exhibiting an area under the ROC curve of 0.74 (95%CI: 0.70-0.77). Based on the corresponding regression coefficients, the prognostic variables were classified as either major (shock, liver disease, anticoagulant therapy, urea/creatinine ratio > 62) or minor (hematocrit < 33%, renal failure, presentation as hematemesis and melenas, systolic arterial pressure < 110 mmHg, regular alcohol consumption, a history of UDB, and a patient age of > 75 years). UDB was predicted to take an unfavorable course in the presence of one major factor or two minor factors. CONCLUSIONS: The proposed algorithm includes pre-endoscopy clinical and laboratory variables, and allows early classification of patients with non-varicose UDB in terms of their possible clinical course.
Adult↗
Can an Algorithm Predict Appropriate Utilization of Emergency Venous Studies?
Venous duplex evaluation (VDE) has virtually supplanted venography in the diagnosis of deep vein thrombosis (DVT). To control low yield of VDE of ambulatory patients, performed at "off-hours," we adopted an algorithm to improve the selection process and to increase efficiency. "Off-hours" studies are those performed after the normal daily working hours, weekends, or holidays. From January 1, 1996, through December 31, 1998, we performed 5393 lower extremities VDE, utilizing color duplex imaging with video taping. 2535 studies were done during the eighteen months prior to adoption of the algorithm on July 1, 1997 and 2858 studies were performed during the subsequent eighteen months. During the first 18 months, 314 requests for emergency studies came from the Emergency Department (ED). 132 were "off-hours" and 24 (18.2%) were positive for DVT compared to 427 after adoption of the algorithm, of which 79 were "off-hours" with 24 being positive for DVT (30.3%). Using an algorithm for dealing with requests for VDE originating in the ED on outpatients at "off-hours" resulted in an overall decrease in requests as well as a greater yield of positive studies without apparent compromise of the quality of care. </hea
Journal Article↗
Prediction algorithm for amino acid types with their secondary structure in proteins (PLATON) using chemical shifts.
The algorithm PLATON is able to assign sets of chemical shifts derived from a single residue to amino acid types with its secondary structure (amino acid species). A subsequent ranking procedure using optionally two different penalty functions yields predictions for possible amino acid species for the given set of chemical shifts. This was demonstrated in the case of the alpha-spectrin SH3 domain and applied to 9 further protein data sets taken from the BioMagRes database. A database consisting of reference chemical shift patterns (reference CSPs) was generated from assigned chemical shifts of proteins with known 3D-structure. This reference CSP database is used in our approach for extracting distributions of amino acid types with their most likely secondary structure elements (namely alpha-helix, beta-sheet, and coil) for single amino acids by comparison with query CSPs. Results obtained for the 10 investigated proteins indicates that the percentage of correct amino acid species in the first three positions in the ranking list, ranges from 71.4% to 93.2% for the more favorable penalty function. Where only the top result of the ranking list for these 10 proteins is considered, 36.5% to 83.1% of the amino acid species are correctly predicted. The main advantage of our approach, over other methods that rely on average chemical shift values is the ability to increase database content by incorporating newly derived CSPs, and therefore to improve PLATON's performance over time.
Algorithms↗
Utility of a web-based breast cancer predictive algorithm for adjuvant chemotherapeutic decision making in a multidisciplinary oncology center.
PURPOSE: Adjuvant drug therapy can extend survival for breast cancer patients, but the balance between costs and benefits may be difficult to estimate. Software programs have been developed for this purpose and recently have become available online. Here, we describe our experience using a web-based program to support adjuvant decision making at a multidisciplinary breast cancer Tumor Board in a university-affiliated oncology center. PATIENTS AND METHODS: One hundred two adjuvant breast cancer cases were discussed by the Tumor Board over a four-month period, with a provisional treatment plan being formulated after each discussion. Program data predicting 10-year risks and benefits were shared with board members after each provisional plan and any change in recommendation was recorded. A user survey was conducted to assess the perceived strengths and weaknesses of the program. RESULTS: Treatment decisions were changed in 12.7 percent of cases (13/102) after consideration of data from the program. Most of these (76.9 percent) were node-negative ER-positive cases, with the most common reason for change being a lower-than-expected added survival benefit from less intensive chemotherapy regimens (ACx4 or CMF; 81.8 percent). In certain recurrent scenarios, the program was perceived to have limitations that led to retention of the original management plan despite data that might otherwise have favored different treatment. On completion of the study period, clinicians' attitudes to the program ranged from enthusiasm to caution. CONCLUSION: Although not replacing clinical judgement, these findings support the value of this web-based program as a decision making adjunct that can help clinicians to separate risk and benefit, compare the added value of different therapeutic interventions in a given clinical context, and present more balanced information about treatment options to patients.
Adult↗
Epitope prediction algorithms for peptide-based vaccine design.
Peptide-based vaccines, in which small peptides derived from target proteins (eptiopes) are used to provoke an immune reaction, have attracted considerable attention recently as a potential means both of treating infectious diseases and promoting the destruction of cancerous cells by a patient's own immune system. With the availability of large sequence databases and computers fast enough for rapid processing of large numbers of peptides, computer aided design of peptide-based vaccines has emerged as a promising approach to screening among billions of possible immune-active peptides to find those likely to provoke an immune response to a particular cell type. In this paper, we describe the development of three novel classes of methods for the prediction problem. We present a quadratic programming approach that can be trained on quantitative as well as qualitative data. The second method uses linear programming to counteract the fact that our training data contains mostly positive examples. The third class of methods uses sequence profiles obtained by clustering known epitopes to score candidate peptides. By integrating these methods, using a simple voting heuristic, we achieve improved accuracy over the state of the art.
Algorithms↗
Predictive algorithms for neuromuscular control of human locomotion.
The problem of quantifying muscular activity of the human body can be formulated as an optimal control problem. The current methods used with large-scale biomechanical systems are non-derivative techniques. These methods are costly, as they require numerous integrations of the equations of motion. Additionally, the convergence is slow, making them impractical for use with large systems. We apply an efficient numerical algorithm to the biomechanical optimal control problem. Using direct collocation with a trapezoidal discretization, the equations of motion are converted into a set of algebraic constraint equations. An augmented Lagrangian formulation is used for the optimization problem to handle both equality and inequality constraints. The resulting min-max problem is solved with a generalized Newton method. In contrast to the prevalent optimal control implementations, we calculate analytical first- and second-derivative information and obtain local quadratic convergence. To demonstrate the efficacy of the method, we solve a steady-state pedaling problem with 7 segments and 18 independent muscle groups. The computed muscle activations compare well with experimental EMG data. The computational effort is significantly reduced and solution times are a fraction of those of the non-derivative techniques.
Algorithms↗
Definition of the immunogenic HLA epitopes based on an epitope prediction algorithm.
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Algorithms↗
Conformation of secondary amides. A predictive algorithm that correlates DFT-calculated structures and experimental proton chemical shifts.
The magnetic deshielding caused by the amido group on CON-CHalpha protons of secondary amides can easily be correlated with DFT-based structures at the B3LYP/6-31G level of theory via a novel algorithm that refines previous models, such as the classical McConnell equation. The shift is given by delta = a + 2.16 cos2(alpha - 35)/d, where alpha denotes the virtual dihedral angle resulting from linking the carbonyl and the alpha-carbons and d is the distance (A) between the shifted proton and the carbonyl oxygen. Notably, in this equation a is a parameter that can be optimized for different solvents, namely, CDCl3, DMSO-d6, and D2O. For the development of these correlations, the preferential conformation of amides is taken from the optimized structures in the gas phase obtained at the DFT level. The deshielding on anti and gauche protons in both rotamers of (Z)-acetamides and E/Z isomers of formamides has been evaluated. This methodology has proved to be highly reliable, allowing us to discard ab initio or DFT conformational arrangements when shifts calculated by the above-mentioned equation differ from the experimental values. Thus, the anti disposition between the CHalpha proton and the N-H bond appears to be the more stable conformation of simple amides. For amides bearing only one proton at Calpha, a local syn minimum can equally be characterized. The rotational barriers around the CON-alkyl bond along with the pyramidalization of the amido group have also been reassessed. As the conformation is taken away from anti or local syn minima, the nonplanarity of the amido group appears to increase.
Journal Article↗
Alloplastic refractive keratophakia: a comparison of predictive algorithms.
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Animals↗
A fast SCOP fold classification system using content-based E-Predict algorithm.
BACKGROUND: Domain experts manually construct the Structural Classification of Protein (SCOP) database to categorize and compare protein structures. Even though using the SCOP database is believed to be more reliable than classification results from other methods, it is labor intensive. To mimic human classification processes, we develop an automatic SCOP fold classification system to assign possible known SCOP folds and recognize novel folds for newly-discovered proteins. RESULTS: With a sufficient amount of ground truth data, our system is able to assign the known folds for newly-discovered proteins in the latest SCOP v1.69 release with 92.17% accuracy. Our system also recognizes the novel folds with 89.27% accuracy using 10 fold cross validation. The average response time for proteins with 500 and 1409 amino acids to complete the classification process is 4.1 and 17.4 seconds, respectively. By comparison with several structural alignment algorithms, our approach outperforms previous methods on both the classification accuracy and efficiency. CONCLUSION: In this paper, we build an advanced, non-parametric classifier to accelerate the manual classification processes of SCOP. With satisfactory ground truth data from the SCOP database, our approach identifies relevant domain knowledge and yields reasonably accurate classifications. Our system is publicly accessible at http://ProteinDBS.rnet.missouri.edu/E-Predict.php.
Algorithms↗
Protein antigen conformation: folding patterns and predictive algorithms; selection of antigenic and immunogenic peptides.
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Antibody Formation↗
A graphic approach to evaluate algorithms of secondary structure prediction.
Algorithms of secondary structure prediction have undergone the developments of nearly 30 years. However, the problem of how to appropriately evaluate and compare algorithms has not yet completely solved. A graphic method to evaluate algorithms of secondary structure prediction has been proposed here. Traditionally, the performance of an algorithm is evaluated by a number, i.e., accuracy of various definitions. Instead of a number, we use a graph to completely evaluate an algorithm, in which the mapping points are distributed in a three-dimensional space. Each point represents the predictive result of the secondary structure of a protein. Because the distribution of mapping points in the 3D space generally contains more information than a number or a set of numbers, it is expected that algorithms may be evaluated and compared by the proposed graphic method more objectively. Based on the point distribution, six evaluation parameters are proposed, which describe the overall performance of the algorithm evaluated. Furthermore, the graphic method is simple and intuitive. As an example of application, two advanced algorithms, i.e., the PHD and NNpredict methods, are evaluated and compared. It is shown that there is still much room for further improvement for both algorithms. It is pointed out that the accuracy for predicting either the alpha-helix or beta-strand in proteins with higher alpha-helix or beta-strand content, respectively, should be greatly improved for both algorithms.
Algorithms↗
High density dental materials and radiotherapy planning: comparison of the dose predictions using superposition algorithm and fluence map Monte Carlo method with radiochromic film measurements.
BACKGROUND AND PURPOSE: During radiotherapy planning high density dental materials create a major challenge in determining correct dose distribution inside patients with head-and-neck tumors. PATIENTS AND METHODS: In this work we investigated the absorbed dose distribution inside a solid water slab phantom with embedded high density material irradiated by a 6MV photon beam of field size 10x10cm. We evaluated the absorbed dose distribution with three different techniques: superposition algorithm, radiochromic film, and the fluence map Monte Carlo (FMMC) method. RESULTS: The results obtained with radiochromic film and FMMC were in good agreement (within +/-5% of the dose) with one another. The superposition algorithm, which is often considered superior to other commercially available dose calculation algorithms, produced appreciably less accurate results than FMMC. In particular, downstream from the high density cerrobend inhomogeneity the superposition algorithm predicts a higher dose than the measurement does by at least 10-16% depending upon the size of the inhomogeneity and the distance from it. Upstream of the high density inhomogeneities the superposition algorithm predicts a lower than measured dose due to its failure to predict the dose enhancement close to the inhomogeneity interface. CONCLUSIONS: The delivered dose downstream from a high density inhomogeneity would be significantly less than the prescribed dose calculated by the superposition algorithm. The FMMC method which is based on a hybrid of the superposition algorithm input fluence data and Monte Carlo can be a useful tool in predicting dose in the presence of high density (e.g. dental) materials.
Algorithms↗
Detecting uber-operons in prokaryotic genomes.
We present a study on computational identification of uber-operons in a prokaryotic genome, each of which represents a group of operons that are evolutionarily or functionally associated through operons in other (reference) genomes. Uber-operons represent a rich set of footprints of operon evolution, whose full utilization could lead to new and more powerful tools for elucidation of biological pathways and networks than what operons have provided, and a better understanding of prokaryotic genome structures and evolution. Our prediction algorithm predicts uber-operons through identifying groups of functionally or transcriptionally related operons, whose gene sets are conserved across the target and multiple reference genomes. Using this algorithm, we have predicted uber-operons for each of a group of 91 genomes, using the other 90 genomes as references. In particular, we predicted 158 uber-operons in Escherichia coli K12 covering 1830 genes, and found that many of the uber-operons correspond to parts of known regulons or biological pathways or are involved in highly related biological processes based on their Gene Ontology (GO) assignments. For some of the predicted uber-operons that are not parts of known regulons or pathways, our analyses indicate that their genes are highly likely to work together in the same biological processes, suggesting the possibility of new regulons and pathways. We believe that our uber-operon prediction provides a highly useful capability and a rich information source for elucidation of complex biological processes, such as pathways in microbes. All the prediction results are available at our Uber-Operon Database: http://csbl.bmb.uga.edu/uber, the first of its kind.
Algorithms↗
Membrane topology of the C-terminal half of the neuronal, glial, and bacterial glutamate transporter family.
Secondary glutamate transporters in neuronal and glial cells in the mammalian central nervous system remove the excitatory neurotransmitter glutamate from the synaptic cleft and prevent the extracellular glutamate concentration to rise above neurotoxic levels. Secondary structure prediction algorithms predict 6 transmembrane helices in the first half of the transporters but fail in the C-terminal half where no clear helix-loop-helix motif is resolved in the hydropathy profile of the primary sequences. A number of previous studies have emphasized the importance of the C-terminal half of the molecules for the function. Here we determine the membrane topology of the C-terminal half of the glutamate transporters by applying the phoA gene fusion technique to the homologous bacterial glutamate transporter of Bacillus stearothermophilus. High sequence conservation and very similar hydropathy profiles in the C-terminal half warrant a similar folding as in the glutamate transporters of the mammalian central nervous system. The C-terminal half contains four putative transmembrane helices. The strong hydrophobic moment and substitution moment of the most C-terminal helix X that point to opposite faces of the helix suggest that the helix faces the lipid environment with its least conserved, hydrophobic face and the interior of the protein with its well conserved, hydrophilic face. Residues that were shown before to be critical for function cluster in helix X and VII.
ATP-Binding Cassette Transporters↗
Identification of candidate sialome components expressed in ixodid tick salivary glands using secretion signal complementation in mammalian cells.
Ixodid ticks manipulate mammalian host pathways by secreting molecules from salivary glands. Novel cDNAs containing functional secretion signals were isolated from ixodid tick salivary glands using a signal sequence trap. Only 15/61 Rhipicephalus appendiculatus and 1/7 Amblyomma variegatum cDNAs had significant identity (< 1e-15) to previously identified sequences. Polypeptides that may interact with host pathways included a kinase inhibitor. Two proteins encoded homologues of the yolk protein vitellogenin and seventeen contained glycine-rich motifs. Four proteins without sequence matches had conserved structural folds, identified using a Threading algorithm. Predicted secretion signals were between fifteen and fifty-seven amino acids long. Four homologous polymorphic proteins contained conserved (26/27 residues) signal peptides. Ten functional tick secretion signals could not be unambiguously identified using predictive algorithms.
Amino Acid Motifs↗