Complex traits and candidate genes: estimation of genetic variance components across multiple genetic architectures

GIOVANNY COVARRUBIAS-PAZARAN Hans-Peter Piepho (2023, [Artículo])

Average Semivariance Linear Mixed Model Variance Component Estimation Polygenic Inheritance Oligogenic Inheritance Mendelian Inheritance CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MENDELISM GENETIC VARIANCE GENOME-WIDE ASSOCIATION STUDIES PHENOTYPES CHROMOSOME MAPPING

Unsupervised segmentation and clustering time series approach to Southern Africa rainfall regime changes

Lovemore  Chipindu Walter Mupangwa Isaiah Nyagumbo Mainassara Zaman-Allah (2023, [Artículo])

Autoregressive Integrated Moving Average Facebook Prophet Hidden Markov Model Regression Regression with Hidden Logistic Process CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA COASTAL AREAS SEMIARID ZONES SUBHUMID ZONES RAINFALL CLIMATE CHANGE

A simple extension to the CMASA method for the prediction of catalytic residues in the presence of single point mutations

David Israel Flores Granados (2014, [Artículo])

The automatic identification of catalytic residues still remains an important challenge in structural bioinformatics. Sequence-based methods are good alternatives when the query shares a high percentage of identity with a well-annotated enzyme. However, when the homology is not apparent, which occurs with many structures from the structural genome initiative, structural information should be exploited. A local structural comparison is preferred to a global structural comparison when predicting functional residues. CMASA is a recently proposed method for predicting catalytic residues based on a local structure comparison. The method achieves high accuracy and a high value for the Matthews correlation coefficient. However, point substitutions or a lack of relevant data strongly affect the performance of the method. In the present study, we propose a simple extension to the CMASA method to overcome this difficulty. Extensive computational experiments are shown as proof of concept instances, as well as for a few real cases. The results show that the extension performs well when the catalytic site contains mutated residues or when some residues are missing. The proposed modification could correctly predict the catalytic residues of a mutant thymidylate synthase, 1EVF. It also successfully predicted the catalytic residues for 3HRC despite the lack of information for a relevant side chain atom in the PDB file. © 2014 Flores et al.

1UU9 protein, 3HRC protein, protein, thymidylate synthase, unclassified drug, protein kinase, thymidylate synthase, accuracy, algorithm, Article, CMASA, CMASA Substitution Matrix, Contact Matrix Average Deviation, controlled study, correlation coeffi CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA MATEMÁTICAS ANÁLISIS NUMÉRICO ANÁLISIS NUMÉRICO