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PubMed1994

Predicting internal exons by oligonucleotide composition and discriminant analysis of spliceable open reading frames.

A new method which predicts internal exon sequences in human DNA has been developed. The method is based on a splice site prediction algorithm that uses the linear discriminant function to combine information about significant triplet frequencies of various functional parts of splice site regions and preferences of oligonucleotides in protein coding and intron regions. The accuracy of our splice site recognition function is 97% for donor splice sites and 96% for acceptor splice sites. For exon prediction, we combine in a discriminant function the characteristics describing the 5'-intron region, donor splice site, coding region, acceptor splice site and 3'-intron region for each open reading frame flanked by GT and AG base pairs. The accuracy of precise internal exon recognition on a test set of 451 exon and 246693 pseudoexon sequences is 77% with a specificity of 79%. The recognition quality computed at the level of individual nucleotides is 89% for exon sequences and 98% for intron sequences. This corresponds to a correlation coefficient for exon prediction of 0.87. The precision of this approach is better than other methods and has been tested on a larger data set. We have also developed a means for predicting exon-exon junctions in cDNA sequences, which can be useful for selecting optimal PCR primers.

Algorithms↗
PubMedDate not supplied

The identification of high-school dropouts identified as learning disabled: evaluating the utility of a discriminant analysis function.

This study examined the utility of a linear discriminant function to distinguish between students identified as learning disabled (LD) who had either been released from high school under codes suggestive of school dropout (n = 213) or graduation (n = 92). The discriminant function was comprised of six variables--student ethnicity, reading ability, family intactness, family socioeconomic status, school transfers, and school-initiated interruptions. The analysis determined that differences between the LD dropout sample and LD graduate sample were sufficient to allow for a discrimination between the groups. On the basis of group differences the discriminant function that was constructed correctly classified 83% of the school dropouts and 46% of the school graduates, for an overall 73% accuracy rate. Those factors contributing most to the function were the number of district-initiated interruptions, school transfers, and family intactness. Based on the findings, implications for school districts and future research are noted.

Achievement↗
PubMed1994

Multivariate discriminant analysis of normal, intraepithelial neoplasia and human papillomavirus infection of the uterine cervix samples.

The present investigation studies the role of multivariate statistical methods on quantitative histopathological features of cells in uterine cervix epithelium to discriminate between normal and abnormal uterine cervix samples. 143 histological specimens were included in the study involving normal cervix, cervical intraepithelial neoplasia (CIN) lesions and cervical human papillomavirus (HPV) infection with and without CIN (condyloma-CIN and condyloma-NCIN groups, respectively). Deep, middle and superficial regions of the cervical squamous epithelium were morphometrically analyzed. Identification of normal cervix from pathological cases was highly achieved with a specificity of 100%. The application of discriminant statistical method within pathological specimens showed an acceptable percentage of cases correctly classified; thus, an efficiency of 83.0% and 74.6% was obtained in order to discriminate within CIN and condyloma-CIN grades respectively. These percentages increased when differentiation between each grade of CIN versus condyloma-CIN were considered, using only 1-3 morphometrical parameters. Our findings indicate that the combination of nuclear and cytoplasmic quantitative features, specially size parameters, permit a high correct percentage classification of cervix samples. The discrimination process was better when few diagnostic categories were included; however, 100% specificity for normal samples was always reached.

Cell Nucleus↗
PubMed1993

The ovarian hyperstimulation syndrome in in-vitro fertilization: a Belgian multicentric study. II. Multiple discriminant analysis for risk prediction.

The considerable overlap of distributions of values for different parameters between control and ovarian hyperstimulation syndrome (OHSS) populations makes any single variable inefficient for risk prediction. Combinations of variables were studied in a discriminant function in order to increase predictivity and decrease the false negative rate. Such analyses were performed on two groups of in-vitro fertilization (IVF) patients: all OHSS cases (n = 128) (group A) and only severe OHSS cases (n = 92) (group B). Progressive introduction and automated stepwise selection of variables were applied to both groups. The best prediction (78.5%) was obtained in group A under post-oocyte retrieval conditions using log oestradiol, slope of log oestradiol increment, human menopausal gonadotrophin (HMG) dosage, number of oocytes retrieved and ratio of luteinizing hormone/follicle stimulating hormone (LH/FSH), in the formula. The corresponding false negative rate was 18.1%. However, effective prevention of OHSS implies the ability to withhold human chorionic gonadotrophin injection. Therefore a formula for pre-oocyte retrieval conditions was established yielding a prediction rate of 76.1% with a false negative rate of 18.1%. To be validated, such formulae have to be applied to another population of IVF cases used as a 'testing-set'.

Belgium↗
PubMed2001

CSF-neurofilament and levodopa tests combined with discriminant analysis may contribute to the differential diagnosis of Parkinsonian syndromes.

The differentiation between Parkinson's disease (PD), progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) is important for prognostic and therapeutic purposes. In order to evaluate the diagnostic capability of two tests reflecting these items, patients fulfilling strict clinical criteria for PD (n=35), MSA (n=36) and PSP (n=14), were consecutively included. An analysis of neurofilament protein (NFL), a marker of axonal degeneration in the cerebrospinal fluid (CSF) and a levodopa test, recorded with optoelectronic technique were performed. Using discriminant analyses, the test's abilities to predict the clinical PD or non-PD (MSA and PSP) diagnoses were compared. Whereas the CSF-NFL and levodopa tests predicted 79 and 85% correct diagnoses respectively, the combined test predicted 90% correct diagnoses. We conclude that the CSF-NFL and levodopa tests provide detailed information of clinical variables on which the clinical diagnostic criteria are based. As they are pathologically unrelated, the diagnostic precision increases compared to clinical diagnoses when they are combined.

Adult↗
PubMed1998

Drug discrimination analysis of pseudoephedrine in rats.

Rats were trained to discriminate amphetamine, 1 mg/kg given intraperitoneally, from saline injection in a two-lever operant drug discrimination task. Pseudoephedrine (a sympathomimetic drug with central and peripheral actions) at doses of 10 mg/kg failed to substitute for amphetamine, at 20 mg/kg partial substitution occurred, while at a 40 mg/kg full substitution was seen. The specificity of the amphetamine cue at the training dose used (1 mg/kg) was shown by the finding that a peripherally acting sympathomimetic drug phenylephrine at doses from 0.2 to 0.8 mg/kg failed to substitute for amphetamine. The potential for abuse of pseudoephedrine administered at high doses is discussed.

Adrenergic alpha-Agonists↗
PubMed1999

A quadratic discriminant analysis of protein structure classification based on the Helix/Strand content.

Based on the 210 non-homologous proteins (domains) classified manually by Michie et al. (J. Mol. Biol. 262, 168-185, 1996), a new structure classification criterion of globular proteins relying on the content of helix/strand has been proposed, using a quadratic discriminant method. Each protein is classified into one of the three classes, i.e. those of alpha class, beta class and alphabeta class (including alpha/beta and alpha+beta classes). According to the new structure classification criterion, of the 210 proteins in the training set, 207 are correctly classified and thus the accuracy is 207/210=98.57%. Multiple cross-validation tests are performed. The jackknife test shows that of the 210 proteins 207 are correctly classified with an accuracy of 98.57%. To test the method further, of 3577 proteins (domains) extracted from SCOP, 91.39% of them are correctly reclassified by the new classification criterion. On average, the accuracy of the new criterion is about 8 percentage points higher than that of the criterion proposed by Nakashima et al. (J. Biochem. 99, 153-162, 1986). Our result shows that the classification based solely on structures is basically consistent with that combining both structural and evolutionary information. Further complete automated classification scheme should consider both structures and evolutionary relationship. The methodology presented provides an appropriate mathematical format to reach this goal.

Animals↗
PubMed2006

Classification of the long-QT syndrome based on discriminant analysis of T-wave morphology.

The long QT syndrome (LQTS) is a genetic disorder, typically characterized by a prolonged QT interval in the ECG due to abnormal cardiac repolarization. LQTS may lead to syncopal episodes and sudden cardiac death. Various parameters based on T-wave morphology, as well as the QT interval itself have been shown to be useful discriminators, but no single ECG parameter has been sufficient to solve the diagnostic problem. In this study we present a method for discrimination among persons with a normal genotype and those with mutations in the KCNQ1 (KvLQT1 or LQT1) and KCNH2 (HERG or LQT2) genes on the basis of parameters describing T-wave morphology in terms of duration, asymmetry, flatness and amplitude. 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.

Adolescent↗
PubMed1989

Ganglion cells in the frog retina: discriminant analysis of histological classes.

Neurons in the ganglion cell layer were studied in Golgi-stained flat-mounted frog (Rana temporaria) retinas. Complementary data were obtained from methylene blue- and HRP-stained retinas. On the basis of qualitative criteria, 55 neurons were ordered into six groups, one class of amacrine cell (A1) and five classes of ganglion cells (G1-G5). A discriminant function analysis based on seven morphological variables resulted in a separation of the cell classes in the space of three axes. The A1 cells are small axonless neurons with knotty and dense dendritic trees. The G1 cells are also small, and apparently very numerous, while the G2 cells are medium-sized neurons with two loose dendritic layers, one vitreal and another (less conspicuous) scleral. The rest of the cells are medium-sized to large neurons with sturdy primary dendrites and more distinct dendritic layers, which in some cells (G3) spread both sclerally and vitreally, in other cells in a single either scleral (G4) or vitreal (G5) layer. The relation between our data and the classification of frog ganglion cells recently presented by Frank and Hollyfield is discussed at length, and in that context problems related to statistical classifications are dealt with. A hypothetical identification of the morphological types with the functional cell classes studied in the Helsinki laboratory is discussed.

Animals↗
PubMed1998

A rapid method to screen for cell-wall mutants using discriminant analysis of Fourier transform infrared spectra.

We have developed a rapid method to screen large numbers of mutant plants for a broad range of cell wall phenotypes using Fourier transform infrared (FTIR) microspectroscopy of leaves. We established and validated a model that can discriminate between the leaves of wild-type and a previously defined set of cell-wall mutants of Arabidopsis. Exploratory principal component analysis indicated that mutants deficient in different cell-wall sugars can be distinguished from each other. Discrimination of cell-wall mutants from wild-type was independent of variability in starch content or additional unrelated mutations that might be present in a heavily mutagenised population. We then developed an analysis of FTIR spectra of leaves obtained from over 1000 mutagenised flax plants, and selected 59 plants whose spectral variation from wild-type was significantly out of the range of a wild-type population, determined by Mahalanobis distance. Cell wall sugars from the leaves of selected putative mutants were assayed by gas chromatography-mass spectrometry and 42 showed significant differences in neutral sugar composition. The FTIR spectra indicated that six of the remaining 17 plants have altered ester or protein content. We conclude that linear discriminant analysis of FTIR spectra is a robust method to identify a broad range of structural and architectural alterations in cell walls, appearing as a consequence of developmental regulation, environmental adaptation or genetic modification.

Arabidopsis↗
PubMed1999

Evaluation of intrauterine growth pattern of twins by linear discriminant analysis of the values of biparietal diameter, femur length and abdominal circumference1.

In a cross-sectional study, the intrauterine growth pattern of 32 twins was compared to that of 205 singletons by analysis of the coefficients of the equations of biparietal diameter (BPD), femur length (FL) and abdominal circumference (AC). Lower values were observed in twins from the 20th week. BPD and AC curves showed a progressively diverging pattern, and yielded different coefficients of equations. AC showed the highest discriminant capacity followed by BPD and FL. Combined values of the two series solved by discriminant function output produced an overlapping of 58%. Based on our data, nomograms of growth of singletons should not be used for twins.

Abdomen↗
PubMed1991

Logistic discriminant analysis improves diagnostic accuracy of exercise testing for coronary artery disease in women.

BACKGROUND: Diagnostic accuracy of the exercise electrocardiogram in women has been shown to be limited for the detection of coronary artery disease. New diagnostic methods based on computer analysis of the exercise electrocardiogram and multivariate analysis have improved the diagnostic value of exercise testing in male subjects. The aim of the present study was to assess whether the diagnostic value of exercise testing can be enhanced in women by using multivariate analysis of exercise data. METHODS AND RESULTS: Between 1978 and 1984, 135 infarct-free women underwent exercise testing and coronary angiography. Significant coronary artery disease was present in 41% of the patients. In this first group, maximal exercise variables were submitted to a stepwise logistic analysis. Work load, heart rate, and ST60X were selected to build a diagnostic model. The model was tested in a second group of 115 catheterized women (significant coronary artery disease in 47%) and of 76 volunteers. We compared the present model with conventional analysis of the exercise electrocardiogram, with ST changes adjusted for heart rate, and with a previously described analysis. In both groups, sensitivity was better with the present model (66% and 70%) than by conventional (68% and 59%) and by the previously described analysis (57% and 44%) without a loss of specificity (85% and 93%). Receiver-operator characteristic curves showed also a better diagnostic accuracy with the present model. CONCLUSIONS: In women, logistic analysis of exercise variables improves the diagnostic value of exercise testing. It yields a significantly better sensitivity without a loss of specificity.

Coronary Disease↗
PubMed1982

Discriminant analysis of pulmonary function parameters. Healthy adults versus mild asthmatics and moderate asthmatics.

Volume-time (V-T) and flow-volume (F-V) curves were measured in all the subjects of nonsmoking young males (mean value 26.3 yrs. of age), healthy and asthmatics. Eleven parameters of pulmonary function tests composed of two V-T, six F-V, and three mean time constant (MTC) parameters, were calculated from the curves. These parameters were used in the two analyses through the all possible selection procedure (APSP) discriminating between healthy adults and mild asthmatics and also between healthy and moderate. Flow rate at 75% of FVC (V75) proved to be the most useful parameter and V50 the next best in both analyses. The probability of misclassification using all eleven parameters was 19.64% in the analysis of healthy adults and mild asthmatics, and 4.29% in the analysis of healthy adults and moderate asthmatics. There was a little difference in the parameters selected at every step. The discriminant analysis proved that the flow-volume patterns were different according to the severity of bronchial asthma. Thus flow-volume recognition was considered to be important in analyzing the severity of bronchial asthma.

Adult↗
PubMed1992

A discriminant analysis applied to methacholine bronchoprovocation testing improves classification of patients as normal, asthma, or COPD.

UNLABELLED: Two discriminant functions, incorporating baseline measurements of pulmonary function and measures of airway responsiveness, were developed to improve patient classification into groups of normal, asthma, or COPD. Accuracy of group classification was compared between the usual laboratory method (single discriminating cut-off) and these new mathematically developed functions. Forty-five normal subjects, 27 asthmatic patients, and ten well-defined COPD patients were entered into the analysis. Measurements of airway responsiveness were determined by measurement of both specific airway conductance (SGaw) and spirometry (FEV1) after sequential inhalation of methacholine. RESULTS: A single discriminant cut-off using measures of SGaw (PD35) or FEV1 (PD20) does not sufficiently discriminate asthma from groups that contain normal and COPD subjects (67 to 71 percent predictive value). On the other hand, our discriminant functions demonstrated improved patient classification (positive predictive value, 88 to 89 percent). We conclude that bronchoprovocation tests used to evaluate the diagnosis of asthma should incorporate measures of baseline lung function into the analysis. This, we believe, is especially necessary when baseline lung function demonstrates minimal airflow obstruction and the possibility of other causes of airway disease exist.

Adult↗
PubMed1991

Electrooculography and discriminant analysis in Duane's syndrome and sixth-cranial-nerve palsy.

Eye-movement recordings may be helpful in the differentiation of Duane's syndrome from sixth-cranial-nerve palsy. Voluntary horizontal saccades were recorded and quantitated by electrooculography in 18 patients with unilateral type I Duane's syndrome and in 25 patients with sixth-nerve palsy. When ranges of abduction were matched, the peak velocities of abducting saccades in affected eyes were decreased equally in both groups. However, the peak velocities of adducting saccades in sound eyes were slowed in patients with Duane's syndrome. Because the standard deviations in saccadic velocities are large, computer-based, stepwise discriminant analyses were performed to identify the variables that proved to be useful in differentiating the two disorders. By entering these variables into the discriminant functions that were created, we could distinguish Duane's syndrome from sixth-nerve palsy in a statistically significant manner.

Abducens Nerve↗