Genomes and Genes
Summary: A statistical analytic technique used with discrete dependent variables, concerned with separating sets of observed values and allocating new values. It is sometimes used instead of regression analysis.
Publications238 found, 100 shown here
- Discriminant analysis of principal components: a new method for the analysis of genetically structured populationsThibaut Jombart
MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College Faculty of Medicine, St Mary s Campus, Norfolk Place, London W21PG, UK
BMC Genet 11:94. 2010..Unfortunately, currently available multivariate methods still lack some essential features needed to study the genetic structure of natural populations...
- Diagnosis of multiple cancer types by shrunken centroids of gene expressionRobert Tibshirani
Department of Health, Research and Policy, and Statistics, Stanford University, Stanford, CA 94305, USA
Proc Natl Acad Sci U S A 99:6567-72. 2002..The technique is general and can be used in many other classification problems. To demonstrate its effectiveness, we show that the method was highly efficient in finding genes for classifying small round blue cell tumors and leukemias...
- Study of on-line adaptive discriminant analysis for EEG-based brain computer interfacesC Vidaurre
Department of Electrical and Electronic Engineering, Public University of Navarre, Campus Arrosadia s n, 31006 Pamplona, Spain
IEEE Trans Biomed Eng 54:550-6. 2007..Two continuously adaptive classifiers were tested: adaptive quadratic and linear discriminant analysis. Three feature types were analyzed, adaptive autoregressive parameters, logarithmic band power estimates ..
- Generalizing discriminant analysis using the generalized singular value decompositionPeg Howland
Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA
IEEE Trans Pattern Anal Mach Intell 26:995-1006. 2004b>Discriminant analysis has been used for decades to extract features that preserve class separability. It is commonly defined as an optimization problem involving covariance matrices that represent the scatter within and between clusters...
- Classification of adolescent psychotic disorders using linear discriminant analysisPatricia J Pardo
The Domenici Research Center for Mental Illness, Brain Sciences Center, Minneapolis Veterans Affairs Medical Center, Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, 55454, USA
Schizophr Res 87:297-306. 2006..The differential diagnosis between schizophrenia and bipolar disorder during adolescence presents a major clinical problem. Can these two diagnoses be differentiated objectively early in the courses of illness?..
- Assessment and comparison of different methods for heartbeat classificationI Jekova
Centre of Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
Med Eng Phys 30:248-57. 2008..the classification abilities of four classification methods--Kth nearest neighbour rule, neural networks, discriminant analysis and fuzzy logic...
- Study of discriminant analysis applied to motor imagery bipolar dataCarmen Vidaurre
Dp IEE, Edificio Los Tejos, Public University of Navarre, Campus Arrosadia s n, Pamplona, 31006, Spain
Med Biol Eng Comput 45:61-8. 2007We present a study of linear, quadratic and regularized discriminant analysis (RDA) applied to motor imagery data of three subjects...
- Subspace projection approaches to classification and visualization of neural network-level encoding patternsRemus Osan
Center for Systems Neurobiology, Department of Pharmacology, Boston University, Boston, Massachusetts, United States of America
PLoS ONE 2:e404. 2007..Here we systematically employed a series of projection methods, such as Multiple Discriminant Analysis (MDA), Principal Components Analysis (PCA) and Artificial Neural Networks (ANN), and compared them with ..
- Decoding subjective preference from single-trial near-infrared spectroscopy signalsSheena Luu
Institute of Biomaterials and Biomedical Engineering, 164 College Street Room 407, University of Toronto, Toronto, Ontario M5S 3G9, Canada
J Neural Eng 6:016003. 2009..Using mean signal amplitudes as features and linear discriminant analysis, we were able to decode which drink was preferred on a single-trial basis with an average accuracy of 80%.
- Differentiating prenatal exposure to methamphetamine and alcohol versus alcohol and not methamphetamine using tensor-based brain morphometry and discriminant analysisElizabeth R Sowell
Laboratory of Neuro Imaging, Department of Neurology, University of California, Los Angeles, Los Angeles, California 90095, USA
J Neurosci 30:3876-85. 2010....
- Selection bias in gene extraction on the basis of microarray gene-expression dataChristophe Ambroise
Laboratoire Heudiasyc, , , France
Proc Natl Acad Sci U S A 99:6562-6. 2002..Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes...
- Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identification from metabolic 1H NMR data setsOlivier Cloarec
Biological Chemistry Section, Faculty of Medicine, Biomedical Sciences Division, Imperial College London, South Kensington, London, UK
Anal Chem 77:1282-9. 2005..of STOCSY with supervised pattern recognition and particularly orthogonal projection on latent structure-discriminant analysis (O-PLS-DA) offers a new powerful framework for analysis of metabonomic data...
- Discriminative feature co-occurrence selection for object detectionTakeshi Mita
Multimedia Laboratory, Corporate Research and Development Center, Toshiba Corporation, Kawasaki, Japan
IEEE Trans Pattern Anal Mach Intell 30:1257-69. 2008....
- Kernel discriminant analysis for positive definite and indefinite kernelsElzbieta Pekalska
School of Computer Science, University of Manchester, Oxford Road, M13 9PL Manchester, UK
IEEE Trans Pattern Anal Mach Intell 31:1017-32. 2009..We illustrate this on artificial and real data for both positive definite and indefinite kernels...
- The use of discriminant analysis and neural networks to forecast the severity of the Poaceae pollen season in a region with a typical Mediterranean climateJuan Antonio Sánchez Mesa
Department of Plant Biology, University of Cordoba, Edificio Celestino Mutis, Campus de Rabanales, E 14071 Cordoba, Spain
Int J Biometeorol 49:355-62. 2005....
- Contribution of artificial neural networks to the classification and treatment of patients with uninvestigated dyspepsiaA Andriulli
Division of Gastroenterology, Casa Sollievo della Sofferenza Hospital, IRCCS, I 71013 San Giovanni Rotondo, Italy
Dig Liver Dis 35:222-31. 2003....
- Use of correspondence discriminant analysis to predict the subcellular location of bacterial proteinsGuy Perrière
Laboratoire de Biometrie et Biologie Evolutive, UMR CNRS no 5558, Universite Claude Bernard Lyon 1, 43, Bd du 11 Novembre 1918, 69622 Villeurbanne Cedex, France
Comput Methods Programs Biomed 70:99-105. 2003Correspondence discriminant analysis (CDA) is a multivariate statistical method derived from discriminant analysis which can be used on contingency tables...
- Short prokaryotic DNA fragment binning using a hierarchical classifier based on linear discriminant analysis and principal component analysisHao Zheng
School of Electrical and Computer Engineering, Georgia Institute of Technology, 210 Technology Circle, Savannah, GA 31407, USA
J Bioinform Comput Biol 8:995-1011. 2010..classifier consists of four layers of local classifiers that are implemented based on the linear discriminant analysis. These local classifiers are responsible for binning prokaryotic DNA fragments into superkingdoms, of the ..
- Identification of peripheral neuropathy in type-2 diabetic subjects by static posturography and linear discriminant analysisS Fioretti
Department of Biomedical, Electronics and Telecommunication Engineering, Universita Politecnica delle Marche, Via Brecce Bianche, Ancona, Italy
Gait Posture 32:317-20. 2010..This study examines whether it is possible to assess the presence of diabetic neuropathy at an early stage by static posturography tests...
- Clustering linear discriminant analysis for MEG-based brain computer interfacesJinyin Zhang
Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
IEEE Trans Neural Syst Rehabil Eng 19:221-31. 2011In this paper, we propose a clustering linear discriminant analysis algorithm (CLDA) to accurately decode hand movement directions from a small number of training trials for magnetoencephalography-based brain computer interfaces (BCIs)...
- Construction of an efficacious model for a nondestructive identification of traditional Chinese medicines Liuwei Dihuang pills from different manufacturers using near-infrared spectroscopy and moving window partial least-squares discriminant analysisHai Yan Fu
State Key Laboratory of Chemo Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China
Anal Sci 25:1143-8. 2009..on the basis of near-infrared spectra (NIRS) coupled with moving window partial least-squares discriminant analysis (MWPLSDA)...
- The use of cluster and discriminant analysis in the investigations of the role of trace metals in the pathogenesis of Parkinson's diseaseJoanna Chwiej
Department of Applied Nuclear Physics, Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Al Mickiewicza 30, 30 059 Krakow, Poland
J Trace Elem Med Biol 24:78-88. 2010..The elemental data were processed using two multivariate techniques, namely cluster and discriminant analysis. The statistical methods were used for data reduction, both unsupervised and supervised classification as ..
- Discriminant analysis of autofluorescence spectra for classification of oral lesions in vivoJ L Jayanthi
Biophotonics Laboratory, Centre for Earth Science Studies, Kerala, India
Lasers Surg Med 41:345-52. 2009..This study evaluates the potential of a multivariate statistical algorithm to classify oral mucosa from autofluorescence spectral features recorded in vivo...
- A classification approach for genotyping viral sequences based on multidimensional scaling and linear discriminant analysisJiwoong Kim
Department of Bioinformatics and Life Sciences, Soongsil University, Seoul, Korea
BMC Bioinformatics 11:434. 2010..Thus, MuLDAS utilizes full spectra of well characterized sequences as references, typically of an order of hundreds, in order to estimate the significance of each genotype assignment...
- Prediction of vocational outcome of people with brain injury after rehabilitation: a discriminant analysisK L Leung
Occupational Therapy Department, MacLehose Medical Rehabilitation Centre, Hospital Authority, Hong Kong, China
Work 25:333-40. 2005..8% of the subjects...
- Multiple correspondence discriminant analysis: an application to detect stratification in copy number variationAlejandro Caceres
Center for research in environmental epidemiology CREAL, Parc de Recerca Biomedica de Barcelona, 88 Doctor Aiguader, Barcelona, Spain
Stat Med 29:3284-93. 2010..In addition, we propose the use of multiple correspondence discriminant analysis (MCDA) to identify an optimal set of copy number variants (CNVs) that correctly infers the population ..
- Faecal pollution source identification in an urbanizing catchment using antibiotic resistance profiling, discriminant analysis and partial least squares regressionS P Carroll
South Burnett Regional Council, Infrastructure Services, Glendon Street, Kingaroy, Queensland, Australia
Water Res 43:1237-46. 2009..b>Discriminant Analysis (DA) was used to differentiate between the ARP of source isolates and to identify the sources of faecal ..
- Study of age-related changes in postural control during quiet standing through linear discriminant analysisGuilherme L Cavalheiro
Biomedical Engineering Laboratory, Faculty of Electrical Engineering, Federal University of Uberlandia, Campus Santa Mônica, Bloco 1E, Av, João Naves de Avila, 2121, Uberlandia, Minas Gerais, 38, 408 100, Brazil
Biomed Eng Online 8:35. 2009..In this context, this study proposes the analysis of the postural control, measured by the displacement of the COP, in groups of young and elderly adults...
- Comparison of linear, nonlinear, and feature selection methods for EEG signal classificationDeon Garrett
Department of Computer Science, Colorado State University, Fort Collins 80523, USA
IEEE Trans Neural Syst Rehabil Eng 11:141-4. 2003..This paper reports the results of a linear (linear discriminant analysis) and two nonlinear classifiers (neural networks and support vector machines) applied to the classification ..
- Application of partial least squares discriminant analysis to two-dimensional difference gel studies in expression proteomicsNatasha A Karp
Department of Biochemistry, University of Cambridge, Cambridge CB2 1QW, UK
Proteomics 5:81-90. 2005..Partial least squares-discriminant analysis (PLS-DA), a multivariate statistical approach, was combined with an iterative threshold process to ..
- Extraction, interpretation and validation of information for comparing samples in metabolic LC/MS data setsPar Jonsson
Research Group for Chemometrics, Department of Chemistry, Umea University, SE 90187 Umea, Sweden
Analyst 130:701-7. 2005..The results showed that the evaluation of the extracted information data using partial least square discriminant analysis (PLS-DA) provided a robust, predictive and transparent model for the metabolic differences between the two ..
- Regularized linear discriminant analysis and its application in microarraysYaqian Guo
Department of Statistics, Stanford University, Stanford, CA 94305, USA
Biostatistics 8:86-100. 2007In this paper, we introduce a modified version of linear discriminant analysis, called the "shrunken centroids regularized discriminant analysis" (SCRDA)...
- Discriminative motif discovery in DNA and protein sequences using the DEME algorithmEmma Redhead
Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, 4072 Australia
BMC Bioinformatics 8:385. 2007....
- MRI characteristics in focal hepatic disease before and after administration of MnDPDP: discriminant analysis as a diagnostic toolThomas K Helmberger
Institute of Clinical Radiology, Klinikum Grosshadern, Ludwig Maximilians University, Marchioninistrasse 15, 81377 Munich, Germany
Eur Radiol 12:62-70. 2002..pre- and post-Mangafodipir trisodium (MnDPDP) administration using a computerized multivariable, discriminant analysis (DA). In a multicenter trial, 151 patients with focal liver disease were studied at 1.5 and 1...
- Conrad: gene prediction using conditional random fieldsDavid DeCaprio
The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
Genome Res 17:1389-98. 2007..Conrad's implementation of SMCRFs advances the state of the art in gene prediction in fungi and provides a robust platform for both current application and future research...
- Multi-class cancer classification via partial least squares with gene expression profilesDanh V Nguyen
Department of Statistics, Texas A and M University, College Station, TX 77843, USA
Bioinformatics 18:1216-26. 2002..The need for multi-class discrimination methodologies is apparent in many microarray experiments where various cancer types are considered simultaneously...
- Discrimination of yeast genes involved in methionine and phosphate metabolism on the basis of upstream motifsDidier Gonze
, , CP 263, Campus Plaine, Blvd du Triomphe, B-1050 Bruxelles, Belgium
Bioinformatics 21:3490-500. 2005..genes with position-specific weight matrices for Pho4p, Met4p/Met28p/Cbf1p and Met31p/Met32p, and applied discriminant analysis to classify genes according to matrix matching scores...
- A new strategy to filter out false positive identifications of peptides in SEQUEST database search resultsJiyang Zhang
College of Mechanical and Electronic Engineering and Automatization, National University of Defense Technology, Changsha, China
Proteomics 7:4036-44. 2007..These results indicate that the new method can reliably control the FPR of peptide identifications and is more sensitive than traditional cutoff-based methods...
- Possible contribution of artificial neural networks and linear discriminant analysis in recognition of patients with suspected atrophic body gastritisEdith Lahner
Digestive and Liver Disease Unit, II Medical School, Sant'Andrea Hospital, University La Sapienza, Rome, Italy
World J Gastroenterol 11:5867-73. 2005....
- Identification of candidate markers associated with agronomic traits in rice using discriminant analysisN Zhang
Department of Agronomy and Environmental Management, LSU AgCenter, Louisiana State University, Baton Rouge, LA 70803, USA
Theor Appl Genet 110:721-9. 2005..We have evaluated the potential of discriminant analysis (DA), a multivariate statistical procedure, to detect candidate markers associated with agronomic traits ..
- Risk factors for addictive disorders: a discriminant analysis on 374 addicted and 513 nonpsychiatric participantsMaurice Corcos
Department of Adolescent Psychiatry of the Institut Mutualiste Monsouris, Paris
Psychol Rep 102:435-49. 2008..Twenty-six risk factors were assessed by interview or self-rating scales. A discriminant analysis determined the respective weight of each risk factor...
- Time-frequency discriminant analysis of MEG signalsMoon ho Ringo Ho
Division of Psychology, School of Humanities and Social Sciences, Nanyang Avenue, Nanyang Technological University, Singapore
Neuroimage 40:174-86. 2008..The method was then applied to magnetoencephalographic data from a standard paired-click paradigm. Discrimination between individuals with schizophrenia and a healthy comparison group confirmed the utility of the method...
- A regularized discriminative model for the prediction of protein-peptide interactionsWolfgang P Lehrach
University of Edinburgh, Edinburgh EH1 2QL, UK
Bioinformatics 22:532-40. 2006..As proposed by Williams, we overcome the problem of susceptibility to over-fitting by adopting a Bayesian a posteriori approach based on a Laplacian prior in parameter space...
- Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics: comparison of discriminant analysis and multiple linear regressionIrini A Doytchinova
Faculty of Pharmacy, Medical University of Sofia, 2 Dunav St, 1000 Sofia, Bulgaria
J Chem Inf Model 47:234-8. 2007..In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for ..
- Linear discriminant analysis of brain tumour (1)H MR spectra: a comparison of classification using whole spectra versus metabolite quantificationK S Opstad
Cancer Research UK Biomedical Magnetic Resonance Research Group, St George s University of London, London, UK
NMR Biomed 20:763-70. 2007..However, the results suggest that a two-step LDA process may help in classifying the five tumour groups to provide optimum classification of MNG with high lipid/macromolecule contributions which maybe misclassified as HG...
- Application of partial least squares discriminant analysis and variable selection procedures: a 2D-PAGE proteomic studyEmilio Marengo
Dipartimento di Scienze dell Ambiente e della Vita, Universita degli Studi del Piemonte Orientale, Via Bellini 25 G, 15100, Alessandria, Italy
Anal Bioanal Chem 390:1327-42. 2008..Here, partial least squares discriminant analysis was applied to improve the results obtained by classic image analysis and to identify the significant ..
- Classification of the long-QT syndrome based on discriminant analysis of T-wave morphologyJ J Struijk
Department of Health Science and Technology, Center for Sensory Motor Interaction, Fredrik Bajers Vej 7D3, 9220, Aalborg, Denmark
Med Biol Eng Comput 44:543-9. 2006..Discriminant analyses based on 4 or 5 parameters both resulted in perfect discrimination in a learning set of 36 subjects. In both cases cross-validation of the resulting classifiers showed no misclassifications either...
- Eigengene-based linear discriminant model for tumor classification using gene expression microarray dataRonglai Shen
Department of Biostatistics, University of Michigan Ann Arbor, MI 48109-0602, USA
Bioinformatics 22:2635-42. 2006..RESULTS: We propose an Eigengene-based Linear Discriminant Analysis (ELDA) to address gene selection in a multivariate framework...
- On counting position weight matrix matches in a sequence, with application to discriminative motif findingSaurabh Sinha
Department of Computer Science, University of Illinois Urbana Champaign, 201 N Goodwin Ave, Urbana, IL 61801, USA
Bioinformatics 22:e454-63. 2006..We finally use the algorithm on genes predictive of social behavior in the honey bee, and find interesting motifs...
- Metabolic profiling of glucuronides in human urine by LC-MS/MS and partial least-squares discriminant analysis for classification and prediction of genderUrsula Lutz
Department of Toxicology, University of Wurzburg, Wurzburg, Germany
Anal Chem 78:4564-71. 2006..female and 10 male students were analyzed by principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) using software SIMCA...
- Discriminant analysis for longitudinal data with multiple continuous responses and possibly missing dataGuillermo Marshall
Departamento de Estadistica, Facultad de Matematicas, Pontificia Universidad Catolica de Chile, Casilla 306, Correo 22, Santiago, Chile
Biometrics 65:69-80. 2009..We present an example using data from a study in 161 pregnant women in Santiago, Chile, where the main interest is to predict normal versus abnormal pregnancy outcomes...
- Global discriminative learning for higher-accuracy computational gene predictionAxel Bernal
Department of Computer and Information Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
PLoS Comput Biol 3:e54. 2007....
- Linear discriminant analysis-based estimation of the false discovery rate for phosphopeptide identificationsXiuxia Du
Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
J Proteome Res 7:2195-203. 2008..A linear discriminant analysis is then performed to determine how to optimally combine peptide scores (in this case, from SEQUEST) into a ..
- Identification of new antimalarial drugs by linear discriminant analysis and topological virtual screeningNassira Mahmoudi
INSERM U511, , , , , Paris, France
J Antimicrob Chemother 57:489-97. 2006..indices were used as structural descriptors and were related to antimalarial activity by using linear discriminant analysis (LDA) and multilinear regression (MLR)...
- Improving model robustness with bootstrapping -- application to optimal discriminant analysis for ordinal responses (ODAO)G Le Teuff
, Centre Hospitalier Universitaire, 1 boulevard Jeanne d'Arc-BP 77908, 21079 Dijon Cedex, France
Methods Inf Med 44:704-11. 2005OBJECTIVE: Recent results published by Coste et al. in discriminant analysis with ordinal responses showed the superiority of optimal discriminating analysis for ordinal responses (ODAO) both in terms of classification and simplicity of ..
- Effective transcription factor binding site prediction using a combination of optimization, a genetic algorithm and discriminant analysis to capture distant interactionsVictor G Levitsky
Institute of Cytology and Genetics SB RAS, Novosibirsk, 630090, Russia
BMC Bioinformatics 8:481. 2007..However, current methods to predict TFBSs are hampered by the high false-positive rates that occur when only sequence conservation at the core binding-sites is considered...
- Effects of MRI acquisition parameter variations and protocol heterogeneity on the results of texture analysis and pattern discrimination: an application-oriented studyMarius E Mayerhoefer
Department of Radiology, MR Center of Excellence, Medical University of Vienna, Waehringer Guertel 18 20, 1090 Vienna, Austria
Med Phys 36:1236-43. 2009..0 T scanner equipped with a microimaging gradient insert coil. Linear discriminant analysis and k nearest neighbor classification were used for texture-based pattern discrimination...
- Selecting informative genes for discriminant analysis using multigene expression profilesXin Yan
Russell Investments, Tacoma, WA, USA
BMC Genomics 9:S14. 2008..However, most of these dimensions are not informative about the between-class difference, and add noises to the discriminant analysis.
- Comparison between discriminant analysis models and "glaucoma probability score" for the detection of glaucomatous optic nerve head changesMichele Iester
Clinica Oculistica, Department of Neurological Sciences, Ophthalmology, Genetic, University of Geno, Genoa, Italy
J Glaucoma 17:535-40. 2008The aim of this study was to evaluate and compare 4 different discriminant analysis formulas and the new Glaucoma Probability Score (GPS) for the detection of morphometric optic nerve head changes in chronic open-angle glaucoma.
- A discriminant analysis extension to mixed modelsL Tomasko
Merck Research Laboratories, Merck and Co, Inc, West Point, PA 19486, USA
Stat Med 18:1249-60. 1999b>Discriminant analysis is commonly used to classify an observation into one of two (or more) populations on the basis of correlated measurements. Classical discriminant analysis approaches require complete data for all observations...
- Class II MHC quantitative binding motifs derived from a large molecular database with a versatile iterative stepwise discriminant analysis meta-algorithmR R Mallios
Medical Information Resources, University of California, San Francisco, 2615 East Clinton Avenue, Fresno, CA 93703, USA
Bioinformatics 15:432-9. 1999..An epitope is a peptide segment that binds to both a T-cell receptor and a major histocompatibility complex (MHC) molecule. Predicting which peptide segments bind MHC molecules is the first step in epitope prediction...
- Use of SHIRPA and discriminant analysis to characterise marked differences in the behavioural phenotype of six inbred mouse strainsD C Rogers
Neuroscience Research, SmithKline Beecham Pharmaceuticals, Harlow, UK
Behav Brain Res 105:207-17. 1999..transgenic and knockout research was carried out using a battery of behavioural tests (SHIRPA) followed by discriminant analysis of the data...
- Recognition of eukaryotic promoters using a genetic algorithm based on iterative discriminant analysisVictor G Levitsky
Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia
In Silico Biol 3:81-7. 2003..The program for promoter recognition is included into the GeneExpress system, section RegScan (http://wwwmgs.bionet.nsc.ru/mgs/programs/proga/)...
- Data reduction using a discrete wavelet transform in discriminant analysis of very high dimensionality dataYinsheng Qu
Cancer Prevention Research Program, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N MP 702 Seattle, Washington, USA
Biometrics 59:143-51. 2003We present a method of data reduction using a wavelet transform in discriminant analysis when the number of variables is much greater than the number of observations...
- Gait analysis to classify external load conditions using linear discriminant analysisMinhyung Lee
Vibration and Acoustics Laboratories, Department of Mechanical Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
Hum Mov Sci 28:226-35. 2009..classification of participants into the correct loading condition was achieved by employing linear discriminant analysis (LDA)...
- Classification of antimicrobial peptide using diversity measure with quadratic discriminant analysisWei Chen
Laboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot, 010021, China
J Microbiol Methods 78:94-6. 2009..In this work, an excellent algorithm of Increment of Diversity with Quadratic Discriminant analysis (IDQD) was proposed to classify antimicrobial peptides with diverse biological activities.
- Striatal antibodies in children with Tourette's syndrome: multivariate discriminant analysis of IgG repertoiresJ T Wendlandt
Department of Neurology, Johns Hopkins University School of Medicine, Harvey 811, 600 N. Wolfe Street, Baltimore, MD 21287-8811, USA
J Neuroimmunol 119:106-13. 2001..A MANOVA differentiated between TS and control blots, and a discriminant analysis demonstrated which variables contributed most to differences between groups...
- Symbolic discriminant analysis of microarray data in autoimmune diseaseJason H Moore
Program in Human Genetics, Vanderbilt University Medical School, Nashville, Tennessee 37232 0700, USA
Genet Epidemiol 23:57-69. 2002..Linear discriminant analysis is a popular multivariate statistical approach for classification of observations into groups...
- Determination of minimum sample size and discriminatory expression patterns in microarray dataDaehee Hwang
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Bioinformatics 18:1184-93. 2002..sample size for discrimination of phenotypic subtypes in a reduced dimensional space obtained by Fisher discriminant analysis (FDA)...
- Predicting class II MHC/peptide multi-level binding with an iterative stepwise discriminant analysis meta-algorithmR R Mallios
Office of Sponsored Projects and Research, University of California, San Francisco, 2615 East Clinton Avenue, Fresno, CA 93703, USA
Bioinformatics 17:942-8. 2001..An agretope is that portion of a peptide that interacts with an MHC molecule. The identification and prediction of agretopes is the first step towards vaccine design...
- Tumor classification by partial least squares using microarray gene expression dataDanh V Nguyen
Center for Image Processing and Integrated Computing, University of California, Davis, CA 95616, USA
Bioinformatics 18:39-50. 2002..Modification of existing statistical methodologies or development of new methodologies is needed for the analysis of microarray data...
- Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and mesotheliomaGavin J Gordon
Division of Thoracic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
Cancer Res 62:4963-7. 2002..Furthermore, we provide evidence suggesting that this technique can be equally accurate in other clinical scenarios...
- Skeletal indicators of locomotor adaptations in living and extinct rodentsJoshua X Samuels
Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California 90095, USA
J Morphol 269:1387-411. 2008..There was also a progressive trend toward increased body size and increased aquatic specialization in the giant beaver lineage (Castoroidinae)...
- Iron-induced oxidative stress in a macrophyte: a chemometric approachSarita Sinha
Ecotoxicology and Bioremediation Group, National Botanical Research Institute, Rana Pratap Marg, Lucknow 226 001, India
Ecotoxicol Environ Saf 72:585-95. 2009..Cluster analysis (CA) rendered two distinct clusters of roots and shoots. Discriminant analysis (DA) identified discriminating variables (NP-SH and APX) between the root and shoot tissues...
- Wavelet-based processing of neuronal spike trains prior to discriminant analysisMark Laubach
John B Pierce Laboratory and Department of Neurobiology, Yale University, 290 Congress Ave, New Haven, CT 06519, USA
J Neurosci Methods 134:159-68. 2004..Recently, statistical pattern recognition methods, such as linear discriminant analysis (LDA), have emerged as a standard approach for examining neural codes...
- Relationship between human genotype and phenotype of N-acetyltransferase (NAT2) as estimated by discriminant analysis and multiple linear regression: 1. Genotype and N-acetylation in vivoP Meisel
Department of Pharmacology, Ernst Moritz Arndt University Greifswald, Germany
Pharmacogenetics 7:241-6. 1997..Application of discriminant analysis allowed the separation of the rapid and slow acetylators solely on the base of their respective mutation ..
- Locating the genes underlying a simulated complex disease by discriminant analysisX Li
Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA
Genet Epidemiol 21:S516-21. 2001..This approach uses the application of either of two methods of standard (stepwise) discriminant analysis to detect linkage based on the differential marker identity-by-descent distributions among the three ..
- Correspondence discriminant analysis: a multivariate method for comparing classes of protein and nucleic acid sequencesG Perrière
Laboratoire de Biometrie, Génétique et Biologie des Populations, UMR CNRS n 5558, Universite Claude Bernard, Lyon, Villeurbanne, France
Comput Appl Biosci 12:519-24. 1996..of a multivariate method for studying classes of nucleotide or protein sequences: correspondence discriminant analysis (CDA)...
- Combining pattern discovery and discriminant analysis to predict gene co-regulationN Simonis
Service de Conformation des Macromolécules Biologiques et Bioinformatique, Centre de Biologie Structurale et Bioinformatique, CP 263, Universite Libre de Bruxelles, Bld du Triomphe B 1050 Bruxelles, Belgium
Bioinformatics 20:2370-9. 2004..We propose a method to discriminate co-regulated from non-co-regulated genes on the basis of counts of pattern occurrences in their non-coding sequences...
- The use of multicomponent statistical analysis in hydrogeological environmental researchNicolaos Lambrakis
Department of Geology, Section of Applied Geology and Geophysics, University of Patras, Patras 26500, Greece
Water Res 38:1862-72. 2004..NO(3)(-) spread in aquifers by applying multicomponent statistical methods (factor, cluster and discriminant analysis) on hydrogeological, hydrochemical, and environmental parameters...
- Feature extraction using recursive cluster-based linear discriminant with application to face recognitionC Xiang
Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576
IEEE Trans Image Process 15:3824-32. 2006..The resulting improvement of performances by the new feature extraction scheme is significant...
- Discriminant subspace analysis: a Fukunaga-Koontz approachSheng Zhang
Department of Electrical and Computer Engineering, University of California at Santa Barbara, CA 93106 9560, USA
IEEE Trans Pattern Anal Mach Intell 29:1732-45. 2007..Furthermore, we extend our our theory to Multiple Discriminant Analysis (MDA)...
- Condensed nearest neighbor data domain descriptionFabrizio Angiulli
Dipartimento di Elettronica Informatica e Sistemistica, Universita della Calabria, Italy
IEEE Trans Pattern Anal Mach Intell 29:1746-58. 2007..A thorough comparison with related methods was accomplished, pointing out the strengths and weaknesses of one-class nearest-neighbor-based training set consistent condensation...
- A study of hippocampal shape difference between genders by efficient hypothesis test and discriminative deformationLuping Zhou
RSISE The Australian National University
Med Image Comput Comput Assist Interv 10:375-83. 2007..This direction is further used in this paper to isolate the discriminative shape difference between classes from the individual variability, achieving a visualization of shape discrepancy...
- Discriminative analysis of brain function at resting-state for attention-deficit/hyperactivity disorderC Z Zhu
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P R China
Med Image Comput Comput Assist Interv 8:468-75. 2005..Moreover, some less reported but highly discriminative regions are also identified. We conclude that the discriminative model has potential ability to improve current diagnosis and treatment evaluation of ADHD...
- BM3 E: discriminative density propagation for visual trackingCristian Sminchisescu
Toyota Technological Institute Chicago, University of Chicago, 1427 East 60th Street, Second Floor, Chicago, IL 60637, USA
IEEE Trans Pattern Anal Mach Intell 29:2030-44. 2007..Our tests on both real and motion capture-based sequences show significant performance gains with respect to competing nearest-neighbor, regression, and structured prediction methods...
- Minimum class variance support vector machinesStefanos Zafeiriou
Aristotle University of Thessaloniki, Thessaloniki 54124, Greece
IEEE Trans Image Process 16:2551-64. 2007..approach is demonstrated by comparing it with the standard SVMs and other classifiers, like kernel Fisher discriminant analysis in facial image characterization problems like gender determination, eyeglass, and neutral facial ..
- Classification of single trial motor imagery EEG recordings with subject adapted non-dyadic arbitrary time-frequency tilingsNuri Firat Ince
Department of Electrical and Electronics Engineering, University of Cukurova, Adana 01330, Turkey
J Neural Eng 3:235-44. 2006..3% on the same subjects, and higher error rates than the proposed approach on each individual subject...
- Face recognition using recursive Fisher linear discriminantC Xiang
Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576
IEEE Trans Image Process 15:2097-105. 2006....
- Incremental linear discriminant analysis for face recognitionHaitao Zhao
Institute of Aerospace Science and Technology, Shanghai Jiao Tong University, Shanghai 200030, China
IEEE Trans Syst Man Cybern B Cybern 38:210-21. 2008..Among the various dimensionality reduction algorithms, linear (Fisher) discriminant analysis (LDA) is one of the popular supervised dimensionality reduction methods, and many LDA-based face ..
- Subclass discriminant analysisManli Zhu
Department of Electrical and Computer Engineering, The Ohio State University, 205 Dreese Lab, 2015 Neil Ave, Columbus, OH 43210, USA
IEEE Trans Pattern Anal Mach Intell 28:1274-86. 2006Over the years, many Discriminant Analysis (DA) algorithms have been proposed for the study of high-dimensional data in a large variety of problems...
- Image classification using correlation tensor analysisYun Fu
Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA
IEEE Trans Image Process 17:226-34. 2008..tensor analysis (CTA), is designed to incorporate both graph-embedded correlational mapping and discriminant analysis in a Fisher type of learning manner...
- Kernel Fisher discriminant for shape-based classification in epilepsyS Kodipaka
Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA
Med Image Anal 11:79-90. 2007..It should be noted that automated identification of hemispherical foci of epilepsy has not been previously reported...
- Volumetric texture segmentation by discriminant feature selection and multiresolution classificationConstantino Carlos Reyes Aldasoro
Department of Computer Science, University of Warwick, CV4 7AL Coventry, UK
IEEE Trans Med Imaging 26:1-14. 2007..The regions segmented from the knees correspond to anatomical structures that can be used as a starting point for other measurements such as cartilage extraction...
- Dendritic spine detection using curvilinear structure detector and LDA classifierYong Zhang
Center for Bioinformatics, Harvard Center for Neurodegeneration and Repair, Harvard Medical School, Boston, MA 02215, USA
Neuroimage 36:346-60. 2007..We evaluate the proposed approach by comparing with the manual results in terms of backbone length, spine number, spine length, and spine density...
- Discriminative learning and recognition of image set classes using canonical correlationsTae Kyun Kim
Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, UK
IEEE Trans Pattern Anal Mach Intell 29:1005-18. 2007..Specifically, inspired by classical Linear Discriminant Analysis (LDA), we develop a linear discriminant function that maximizes the canonical correlations of within-class ..
- Simultaneous registration and parcellation of bilateral hippocampal surface pairs for local asymmetry quantificationNicholas A Lord
University of Florida, Gainesville, FL 32611, USA
IEEE Trans Med Imaging 26:471-8. 2007..We present examples using both synthetic data and pairs of left and right hippocampal structures and demonstrate the relevance of the extracted features through a clinical epilepsy classification analysis...
- Bagging linear sparse Bayesian learning models for variable selection in cancer diagnosisChuan Lu
Department of Computer Science, University of Wales, Aberystwyth SY23 3DB, UK
IEEE Trans Inf Technol Biomed 11:338-47. 2007..The work is experimentally compared to other VS methods. It is shown that the use of bagging can improve the reliability and stability of both VS and model prediction...
- Automated discrimination of tissue boundaries using ultrasound images of "ubiquitous echo"Masahiro Inoue
Graduate Schools Science and Engineering Information Science, Saga University, 1 Honjo Machi, Saga, Saga, 840 8502, Japan
Conf Proc IEEE Eng Med Biol Soc 2007:1330-4. 2007..Experimental results show that the proposed method can achieve considerably high discrimination performance...
- Large deformation diffeomorphism and momentum based hippocampal shape discrimination in dementia of the Alzheimer typeLei Wang
Department of Psychiatry, Washington University School of Medicine, Campus Box 8134, 660 S Euclid Ave, St Louis, MO 63110, USA
IEEE Trans Med Imaging 26:462-70. 2007..Further, PCA of the initial momentum leads to correct classification of 12 out of 18 DAT subjects and 22 out of 26 control subjects...
- Tracking in low frame rate video: a cascade particle filter with discriminative observers of different life spansYuan Li
Department of Computer Science, University of Southern California, Los Angeles, CA 90089, USA
IEEE Trans Pattern Anal Mach Intell 30:1728-40. 2008..Experiments show significantly improved accuracy of the proposed approach in comparison with existing tracking methods, under the condition of LFR data and abrupt motion of both target and camera...
- Speech Intelligibility Testing in Children with Repaired Cleft PalateDavid Zajac; Fiscal Year: 2007..Multiple regression and descriptive discriminant analysis techniques will be employed...
- Risk for Workplace Violence in Long-Haul TruckersDebra Anderson; Fiscal Year: 2004..Dependent on the specific aim, bivariate relationships, logistic regression, discriminant analysis, Cronbach's alpha, and ANCOVA will be used...
- Rett syndrome: determinants of outcome and burdenHelen Leonard; Fiscal Year: 2007..regression models to examine effects of different variables on child and family level outcomes and discriminant analysis, recursive partitioning and machine learning to identify genotype/phenotype associations at the individual ..
- Proteomics Approaches to Interstitial Cystitis.Brian Liu; Fiscal Year: 2006..e., hierarchical cluster analysis and K-means methods, canonical correlations, discriminant analysis, Bayesian statistics, self-organizing maps and neural networks) that can stratify samples according to ..
- Metabolomic and Isotopomer Analysis of Xenobiotic StressHenri Brunengraber; Fiscal Year: 2009..A number of techniques will be evaluated, including Principal Component Analysis, Fisher Discriminant Analysis and Partial Least Squares. 2...
- Three-Class ROC Analysis for Task-Based Medical Image Quality AssessmentXin He; Fiscal Year: 2007..proposed a three- class ROC analysis method that extends and unifies the decision theoretic, linear discriminant analysis and probabilistic foundations of binary ROC in a three-class paradigm...
- MEDICALLY TREATED AND FATAL SUICIDE ACTS: NUMBER & COSTTed Miller; Fiscal Year: 2002..2) Using the pooled state data and CHAID tree-building tools, to develop and validate a discriminant analysis model for estimating injury causes from national or state hospital discharge data without E-codes...
- Adipose Metabolic Profiling for Obesity Drug TargetingKyongbum Lee; Fiscal Year: 2005..parallel metabolic flux libraries using established modeling methodologies, d) Perform multivariate discriminant analysis on the metabolite and flux libraries to identify significant markers for each of the growth conditions...
- AUDITORY TEMPORAL PROCESSES, SPEECH PERCEPTION AND AGINGSandra Gordon Salant; Fiscal Year: 1993..mos. 49-60) applies discriminant analysis statistical techniques to formulate profiles of temporal processing abilities of young and elderly ..
- METHAMPHETAMINE ABUSE--NATURAL HISTORY,TREATMENT EFFECTSMary Lynn Brecht; Fiscal Year: 2000..include descriptive measures, analysis of variance (ANOVA) and MANOVA, loglinear modeling, regression and discriminant analysis, survival methods, Markov models, and structural equation modeling...
- Computational tools for T- and B-cell epitope predictionWerner A Braun; Fiscal Year: 2010..will be used in combination with a partial least squares approach to reduce the number of variables in the discriminant analysis and in artificial neural networks...
- A Virtual Reality Environment for Genomic Data VisualizationFatima Merchant; Fiscal Year: 2007..select among a number of data projection techniques, including principal component analysis (PCA), linear discriminant analysis (LDA), singular value decomposition (SVD), multi-dimensional scaling (MDS), projection pursuit (PP), self-..
- Tree Ensemble Regression and Classification MethodsJAMES SCHIMERT; Fiscal Year: 2004..This proposed software will enable medical researchers to obtain high prediction accuracy, and complement traditional tools like discriminant analysis, linear and logistic regression models, and the Cox model.
- DEVELOPMENT OF SLEEP STATES AND SIDS RISKRonald Harper; Fiscal Year: 1993..Multivariate statistical procedures, including stepwise logistic regression and discriminant analysis, will also be used to assess differences among risk groups.
- ELECTROPHYSIOLOGY OF CANNABINOID ACTION ON RAT BEHAVIORSJing Yu Chang; Fiscal Year: 2001..Ensemble activity of many neurons in relation to behavioral events will be examined using discriminant analysis. The goal of this research is to test the hypothesis that cannabinoids act to selectively disrupt ..
- STATISTICAL METHODS FOR GENE MAPPINGKenneth L Lange; Fiscal Year: 2010..apply these methods to estimation in random graphs, nonnegative matrix factorization, and multicategory discriminant analysis. These methods are also pertinent to fast logistic regression with case-control data and fast mapping of ..
- STATISTICAL METHODS FOR GENE MAPPINGKenneth L Lange; Fiscal Year: 2010..apply these methods to estimation in random graphs, nonnegative matrix factorization, and multicategory discriminant analysis. These methods are also pertinent to fast logistic regression with case-control data and fast mapping of ..
- STATISTICAL METHODS FOR GENE MAPPINGKenneth Lange; Fiscal Year: 2009..apply these methods to estimation in random graphs, nonnegative matrix factorization, and multicategory discriminant analysis. These methods are also pertinent to fast logistic regression with case-control data and fast mapping of ..