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Start Over Author "Mele, B." Publisher springer science and business media llc
18 results on '"Mele, B."'

2. Umgang mit gerinnungshemmenden Substanzen in der Ophthalmochirurgie – eine Umfrage unter Ophthalmochirurgen in Deutschland

Author

Feltgen, N., primary, Mele, B., additional, Dietlein, T., additional, Erb, C., additional, Eckstein, A., additional, Hager, A., additional, Heiligenhaus, A., additional, Helbig, H., additional, Hoerauf, H., additional, Hoffmann, E., additional, Pauleikhoff, D., additional, Schittkowski, M., additional, Seitz, B., additional, Sucker, C., additional, Suffo, S., additional, Schaudig, U., additional, Tost, F., additional, Thurau, S., additional, Walter, P., additional, and Koscielny, J., additional

Published
2018
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7. From the LHC to future colliders

Author

De Roeck, A., primary, Ellis, J., additional, Grojean, C., additional, Heinemeyer, S., additional, Jakobs, K., additional, Weiglein, G., additional, Wells, J., additional, Azuelos, G., additional, Dawson, S., additional, Gripaios, B., additional, Han, T., additional, Hewett, J., additional, Lancaster, M., additional, Mariotti, C., additional, Moortgat, F., additional, Moortgat-Pick, G., additional, Polesello, G., additional, Riemann, S., additional, Schumacher, M., additional, Assamagan, K., additional, Bechtle, P., additional, Carena, M., additional, Chachamis, G., additional, Chen, K. F., additional, De Curtis, S., additional, Desch, K., additional, Dittmar, M., additional, Dreiner, H., additional, Dührssen, M., additional, Foster, B., additional, Frandsen, M. T., additional, Giammanco, A., additional, Godbole, R., additional, Gopalakrishna, S., additional, Govoni, P., additional, Gunion, J., additional, Hollik, W., additional, Hou, W. S., additional, Isidori, G., additional, Juste, A., additional, Kalinowski, J., additional, Korytov, A., additional, Kou, E., additional, Kraml, S., additional, Krawczyk, M., additional, Martin, A., additional, Milstead, D., additional, Morton-Thurtle, V., additional, Moenig, K., additional, Mele, B., additional, Ozcan, E., additional, Pieri, M., additional, Plehn, T., additional, Reina, L., additional, Richter-Was, E., additional, Rizzo, T., additional, Rolbiecki, K., additional, Sannino, F., additional, Schram, M., additional, Smillie, J., additional, Sultansoy, S., additional, Tattersall, J., additional, Uwer, P., additional, Webber, B., additional, and Wienemann, P., additional

Published
2010
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18. Challenging popular tools for the annotation of genetic variations with a real case, pathogenic mutations of lysosomal alpha-galactosidase

Author

Giuseppina Andreotti, Bruno Hay Mele, Ludovica Liguori, Maria Vittoria Cubellis, Valentina Citro, Chiara Cimmaruta, Cimmaruta, Chiiara, Citro, V., Andreotti, G., Liguori, L., Cubellis, M. V., and Hay Mele, B.

Subjects
0301 basic medicine, Bioinformatics, In silico, Mutation, Missense, rare disease, macromolecular substances, Computational biology, Disease, Biology, lcsh:Computer applications to medicine. Medical informatics, Biochemistry, 03 medical and health sciences, 0302 clinical medicine, Structural Biology, Variant analysis, Genetic variation, Genotype, medicine, Humans, clinical informatic, Missense mutation, lcsh:QH301-705.5, Molecular Biology, Exome, Bioinformatic, Fabry disease, Research, Applied Mathematics, Molecular Sequence Annotation, medicine.disease, Clinical informatics, Variant analysi, Lysosome, Phenotype, Computer Science Applications, 030104 developmental biology, lcsh:Biology (General), alpha-Galactosidase, lcsh:R858-859.7, Lysosomes, 030217 neurology & neurosurgery, Human
Abstract

Background Severity gradation of missense mutations is a big challenge for exome annotation. Predictors of deleteriousness that are most frequently used to filter variants found by next generation sequencing, produce qualitative predictions, but also numerical scores. It has never been tested if these scores correlate with disease severity. Results wANNOVAR, a popular tool that can generate several different types of deleteriousness-prediction scores, was tested on Fabry disease. This pathology, which is caused by a deficit of lysosomal alpha-galactosidase, has a very large genotypic and phenotypic spectrum and offers the possibility of associating a quantitative measure of the damage caused by mutations to the functioning of the enzyme in the cells. Some predictors, and in particular VEST3 and PolyPhen2 provide scores that correlate with the severity of lysosomal alpha-galactosidase mutations in a statistically significant way. Conclusions Sorting disease mutations by severity is possible and offers advantages over binary classification. Dataset for testing and training in silico predictors can be obtained by transient transfection and evaluation of residual activity of mutants in cell extracts. This approach consents to quantitative data for severe, mild and non pathological variants. Electronic supplementary material The online version of this article (10.1186/s12859-018-2416-7) contains supplementary material, which is available to authorized users.

Published
2018

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