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At least 595 records · Page 33Linked to original sources
PubMed1991

Cloning of the maize rough dwarf virus genome: molecular confirmation of the plant-reovirus classification scheme and identification of two large nonoverlapping coding domains within a single genomic segment.

The segmented double-stranded RNA genome of maize rough dwarf virus, a plant-infecting reovirus of the genus Fijivirus, was cloned and partially characterized. Nucleotide sequence analysis of full-length cDNA clones corresponding to genomic segments S6, S7, and S8 revealed each segment to contain the conserved terminal oligonucleotide sequences (+) 5' AAGUUUUUU------UGUC 3' and adjacent, segment-specific, regions of inverted complementarity (inverted repeats), a structural motif previously reported for members of the genus Phytoreovirus. Genomic segment S6 was completely sequenced and found to consist of 2193 base pairs. Computer analysis indicated that the coding strand contained two large nonoverlapping open reading frames consisting of 363 and 310 codons and located in the 5'- and 3'-terminal domains, respectively. This was confirmed by cell-free translation studies with synthetic transcripts and denatured genomic RNA. However, only the product of the 5'-proximal open reading frame, a 40-kDa polypeptide, was efficiently expressed in vitro from the full-length S6 coding strand. This represents the first case in which a reovirus genomic segment was found to contain two large open reading frames in a nonoverlapping configuration, suggesting possible alternative strategies for regulation of gene expression by members of this genus. The combined results provide a molecular confirmation of the current classification scheme for plant-infecting reoviruses. Furthermore, the fact that the same terminal structural motif is conserved across genera provides additional evidence that these elements serve an important functional role during genome transcription or replication.

Amino Acid Sequence↗
PubMed1993

Molecular methods for the detection and classification of Cryptosporidium.

Cryptosporidiosis is a zoonotic disease caused by a parasitic protozoan belonging to the coccidial genus Cryptosporidium. Current laboratory methods are adequate for the detection of the infection when oocysts are present in great numbers, but more-sensitive means of identification are urgently required. In a recent issue of Parasitology Today, Carolyn Petersen has presented a review of the cell biology of this parasite'. Here, Kath Webster draws attention to the various methods involved in its detection and classification.

Journal Article↗
PubMed2003

Classification of follicular thyroid tumors by molecular signature: results of gene profiling.

PURPOSE: Thyroid nodules are common, with a lifetime risk of developing a clinically significant thyroid nodule of 10% or higher. Preoperative diagnosis was greatly enhanced by the introduction of fine needle aspiration in the 1970s, but there has been little advancement since that time. Discrimination between benign and malignant follicular neoplasms is currently not possible by fine needle aspiration and can even be difficult after full pathologic review. The purpose of these studies is to identify genes expressed in follicular adenomas and carcinomas of the thyroid that will permit molecular differentiation of these neoplasms. EXPERIMENTAL DESIGN: Gene expression patterns of 17 thyroid follicular tumors were analyzed by oligonucleotide array analysis. Gene profiles for follicular adenomas and carcinomas were identified, and the two groups were compared for differences in expression levels. The differentially expressed genes were used to perform a hierarchical clustering analysis training set. Five follicular tumors with diagnosis undisclosed to the investigators and 2 minimally invasive carcinomas were entered into the cluster analysis as a test set to determine whether diagnosis by gene profile correlated with that obtained by pathologic evaluation. RESULTS: Thyroid follicular adenomas and carcinomas showed strikingly distinct gene expression patterns. The expression patterns of 105 genes were found to be significantly different between follicular adenoma and carcinoma. Many uncharacterized genes contributed to the distinction between tumor types. For five follicular tumors for which the final diagnosis was undisclosed, the clustering algorithm gave the correct diagnosis in all 5 cases. CONCLUSIONS: Gene profiling is a useful tool to predict the molecular diagnosis of follicular thyroid tumors. Genes were identified that reliably differentiate follicular thyroid carcinoma from adenoma. This study provides insight into genes that may be important in the molecular pathogenesis of follicular thyroid tumors, as well candidates for preoperative diagnosis of follicular thyroid carcinoma.

Adenocarcinoma, Follicular↗
PubMed2002

Identification of combination gene sets for glioma classification.

One goal for the gene expression profiling of cancer tissues is to identify signature genes that robustly distinguish different types or grades of tumors. Such signature genes would ideally provide a molecular basis for classification and also yield insight into the molecular events underlying different cancer phenotypes. This study applies a recently developed algorithm to identify not only single classifier genes but also gene sets (combinations) for use as glioma classifiers. Classifier genes identified by this algorithm are shown to be strong features by conservatively and collectively considering the misclassification errors of the feature sets. Applying this approach to a test set of 25 patients, we have identified the best single genes and two- to three-gene combinations for distinguishing four types of glioma: (a) oligodendroglioma; (b) anaplastic oligodendroglioma; (c) anaplastic astrocytoma; and (d) glioblastoma multiforme. Some of the identified genes, such as insulin-like growth factor-binding protein 2, have been confirmed to be associated with one of the tumor types. Using combinations of genes, the classification error rate can be significantly lowered. In many instances, neither of the individual genes of a two-gene set performs well as an accurate classifier, but the combination of the two genes forms a robust classifier with a small error rate. Two-gene and three-gene combinations thus provide robust classifiers possessing the potential to translate expression microarray results into diagnostic histopathological assays for clinical utilization.

Algorithms↗
PubMed1979

Classification of drugs by discriminant analysis using fragment molecular connectivity values.

An investigation was made into the use of linear and quadratic discriminant analysis, along with K nearest-neighbor analysis, in the classification of a set of 51 compounds which were divided into five therapeutic categories. By superimposing each compound on a pattern structure, as first proposed by Cammarata, eight positions were assigned on the molecule. Each position was coded with the numerical value of a descriptor index. Relative molar refraction, which was the index used by Cammarata, was compared with a number of molecular connective indices. For each of the indices studied, it was found that only four of the eight positions contributed significantly to between-class differences. It was also found that first-order molecular connectivity, calculated as the sum of the contributions of each of the bonds joining a given position, resulted in consistently fewer misclassifications as compared with the other indices. Using first-order molecular connectivity, validation procedures were performed on the original set of compounds, on random samples drawn from this set, and on a set of ten compounds not included in the analysis. The results obtained were highly data dependent, but they, nevertheless, suggest that molecular connectivity indices should prove useful in structural classification procedures.

Analysis of Variance↗
PubMedDate not supplied

Clustering chemical databases using adaptable projection cells and MCS similarity values.

In this paper we propose a new method based on measurements of the structural similarity for the clustering of chemical databases. The proposed method allows the dynamic adjustment of the size and number of cells or clusters in which the database is classified. Classification is carried out using measurements of structural similarity obtained from the matching of molecular graphs. The classification process is open to the use of different similarity indexes and different measurements of matching. This process consists of the projection of the obtained measures of similarity among the elements of the database in a new space of similarity. The possibility of the dynamic readjustment of the dimension and characteristic of the projection space to adapt to the most favorable conditions of the problem under study and the simplicity and computational efficiency make the proposed method appropriate for its use with medium and large databases. The clustering method increases the performance of the screening processes in chemical databases, facilitating the recovery of chemical compounds that share all or subsets of common substructures to a given pattern. For the realization of the work a database of 498 natural compounds with wide molecular diversity extracted from SPECS and BIOSPECS B.V. free database has been used.

Journal Article↗
PubMed2001

Characterisation of molecular alterations in microdissected archival gliomas.

Classification of gliomas according to their molecular characteristics may be important in future histopathological diagnosis. However, gliomas frequently display heterogeneity at the histological, biological and molecular level. In this study of archival diagnostic gliomas, precision microdissection was used to enrich samples in the most malignant cells or to investigate intratumoural histological heterogeneity. Analysis of tumour samples microdissected from the most aggressive regions, representative of the histopathological diagnosis, revealed PTEN mutations in 4/14 anaplastic astrocytomas, 4/13 glioblastomas and 1 gliosarcoma, but not in 19 low-grade gliomas. Using a novel PCR procedure and direct sequence analysis of the entire coding sequence, TP53 mutations were detected in 1/3 pilocytic astrocytomas, 3/13 astrocytomas, 4/14 anaplastic astrocytomas, 5/13 glioblastomas and 1 gliosarcoma. All but one of the tumours with TP53 mutation showed p53 immunopositivity, but 5 low-grade and 10 high-grade gliomas had p53 protein nuclear accumulation in the absence of detectable mutation. p53 status was unrelated to p21 expression. Neither PTEN nor TP53 mutations influenced the proliferative index or microvessel density of high-grade astrocytomas. Unusual findings include: TP53 mutation in a juvenile pilocytic astrocytoma; TP53 and PTEN mutations in a de novo glioblastoma, a gliosarcoma with identical mutations in gliomatous and sarcomatous components, and an infratentorial anaplastic astrocytoma with an earlier supratentorial grade II astrocytoma bearing the same TP53 mutation but not the PTEN mutation or loss of heterozygosity (LOH) of 10q23. Similarly, the transition to high-grade histology was associated with acquisition of PTEN mutations and 10q23.3 LOH in two de novo high-grade tumours with regions of low-grade histology.

Adolescent↗
PubMed1976

[Notes about molecular weights of aroma compounds].

Classification of 2000 food aroma compounds as to their molecular weight shows an accumulation in the range of 135 to 155, and an upper limit of 310. Molecular masses of substances with high aroma effectiveness are below 200. As aroma compounds are composed only of the elements C, H, O, N and S, even numbers of molecular masses predominate among these substances. A periodicity with an interval of 7 units of molecular mass observed seems to be caused by the presence of complete homologuous series of compounds within the range of low molecular masses.

Flavoring Agents↗
PubMed2001

QSAR and chemometric approaches for setting water quality objectives for dangerous chemicals.

In order to evaluate environmentally safe levels of dangerous chemicals, there is the need for a set of toxicological data on organisms representative of the ecosystems, which is often unavailable or inadequate. In this article, a predictive approach was applied to a set of 125 chemicals (derived from the European priority list in compliance with Directive 76/464/EEC), for which water quality objectives were available. Toxicological data on organisms representative of the aquatic environment (algae, Daphnia, and fish) were taken from the literature or predicted by means of quantitative structure--activity relationships. This provided toxicological data on all three organisms for 97 of 125 chemicals and on at least two organisms (Daphnia and fish) for the whole data set. Principal Component Analysis was applied in order to perform an a priori classification of chemicals based on toxicity data. Then several classification models, based on traditional and nontraditional molecular descriptors, were applied. Classification models gave results in agreement with the a priori classification as well as with the original water quality objectives classification. The behavior of some outliers was explained. The approach described appears to be a useful tool for the preliminary classification of chemicals that are dangerous to the aquatic environment for which toxicological data are inadequate.

Animals↗
PubMed1994

[Hereditary epidermolysis bullosa: towards classification and genetic counseling based upon identification of molecular defects].

Inherited epidermolysis bullosa (EB) includes three main types depending on the precise ultrastructural level at which the split responsible for the blistering occurs; 1) simplex EB (SEB) located at the level of the basal cells; 2) junctional EB (JEB) located in the lamina lucida; 3) dystrophic EB (DEB) located in the dermis below the lamina densa at the level of the anchoring fibrils. The authors review the major recent progresses which have led to the identification of the genes and of several molecular defects in these three types, such as: mutations of the genes of keratins 5 and 14 in SEB, molecular defects in the gamma 2 chain gene of nicein/kalinin coding for the anchoring fibrils in JEB, abnormalities of the collagen VII gene coding for the anchoring fibrils in DEB. These data allow to consider a classification of EB based on molecular defects. They also have important consequences for genetic counselling and prenatal diagnosis for the families presenting an affected child.

Cell Adhesion Molecules↗
PubMedDate not supplied

Classification of glioblastoma multiforme in adults by molecular genetics.

Recent advances in cytogenetic and molecular methodologies have elucidated certain principal characteristics of oncogenesis in glioblastoma multiforme. The earliest clues implicate gene sequence alterations, such as gene amplification and numerical gain or loss of function in specific chromosomes. Genetic classification and expression patterns have thus been constructed, conferring the likelihood of two types of glioblastoma, primary (de novo) as opposed to secondary (evolving from a pre-existing low-grade glioma). The former group of tumors exhibits more frequent occurrences of EGFR gene amplification, whereas the latter group relies strongly on TP53 gene inactivation. Many other tumor suppressor genes and oncogenes have been discovered. Most gene alterations induce cell cycle dysfunction on a complex molecular level. Further insight into tumor genesis by means of genomic assays may aid in predicting the clinical behavior of glioblastoma and in providing individualized potential targets for therapeutic agents.

Brain Neoplasms↗
PubMed2002

Molecular diagnosis of human enteroviruses by phylogeny-based classification by use of the VP4 sequence.

Human enteroviruses (EVs) are the major cause of a variety of acute and chronic illnesses. Virus isolation and neutralization tests are usually done to identify the causative virus, but these tests are labor intensive, time consuming, and sometimes require suckling mice from which certain viruses have been isolated. This study investigated a rapid and reliable method based on reverse-transcription polymerase chain reaction and phylogenetic analysis. The phylogenetic tree constructed by neighbor-joining on the basis of the VP4 sequence from 66 prototypes grouped all human EVs into 5 distinct clusters. These clusters correspond closely to the 5 newly designated species-human EV A-D and poliovirus. The VP4 sequences of 89 isolates from 26 serotypes obtained over >30 years plus those of 66 prototype strains were analyzed. Each isolate formed a monophyletic cluster along with its respective prototype strain, allowing for serotype identification (with the exception of E-8). VP4-based classification appears to be an effective tool for the molecular epidemiology study of EVs.

Capsid↗
PubMed2000

Pharmacological classification of drugs based on neural network processing of molecular modeling data.

The performance of artificial neural network (ANN) models in predicting pharmacological classification of structurally diverse drugs based on their theoretical chemical parameters was demonstrated. The classification coefficients for psychotropic agents, beta-adrenolytic drugs, histamine H(1) receptor antagonists and drugs binding to alpha-adrenoceptors were 100, 100, 95 and 86%, respectively. A set of easily accessible non-empirical molecular parameters describing the structure of xenobiotics can provide information allowing the prediction of some pharmacological properties of drugs and drug candidates employing ANN models. Since ANN analysis can help cluster as well as segregate drugs and drug candidates according to their known and expected pharmacological properties, the number of routine biological assays might be reduced. The results presented here might be used to improve the efficiency of high throughput screening programs for new drug hits by demonstrating a promising procedure for diverse combinatorial library design and evaluation.

Models, Molecular↗
PubMed1991

Molecular structure matching by simulated annealing. IV. Classification of atom correspondences in sets of dissimilar molecules.

A set of 6 molecules, active at the benzodiazepine GABAA site are matched pairwise with one member of the set in turn. Matchings are performed by simulated annealing using null correspondences to reject poorly matched atom positions. Cluster analysis is employed to identify molecular similarities after an optimal molecular superimposition has been discovered. A statistic for the compactness of clustered atom positions is suggested. The introduction of null correspondences causes the clusters of matched atoms to become more compact.

Benzodiazepines↗
PubMed2003

Tissue microarray study for classification of breast tumors.

Clinical and pathological heterogeneity of breast cancer hinders selection of appropriate treatment for individual cases. Molecular profiling at gene or protein levels may elucidate the biological variance of tumors and provide a new classification system that correlates better with biological, clinical and prognostic parameters. We studied the immunohistochemical profile of a panel of seven important biomarkers using tumor tissue arrays. The tumor samples were then classified with a monothetic (binary variables) clustering algorithm. Two distinct groups of tumors are characterized by the estrogen receptor (ER) status and tumor grade (p = 0.0026). Four biomarkers, c-erbB2, Cox-2, p53 and VEGF, were significantly overexpressed in tumors with the ER-negative (ER-) phenotype. Eight subsets of tumors were further identified according to the expression status of VEGF, c-erbB2 and p53. The malignant potential of the ER-/VEGF+ subgroup was associated with the strong correlations of Cox-2 and c-erbB2 with VEGF. Our results indicate that this molecular classification system, based on the statistical analysis of immunohistochemical profiling, is a useful approach for tumor grouping. Some of these subgroups have a relative genetic homogeneity that may allow further study of specific genetically-controlled metabolic pathways. This approach may hold great promise in rationalizing the application of different therapeutic strategies for different subgroups of breast tumors.

Algorithms↗