about
BETAWARE: a machine-learning tool to detect and predict transmembrane beta-barrel proteins in prokaryotes.Improving the detection of transmembrane β-barrel chains with N-to-1 extreme learning machines.BCov: a method for predicting β-sheet topology using sparse inverse covariance estimation and integer programming.INPS: predicting the impact of non-synonymous variations on protein stability from sequence.Large scale analysis of protein stability in OMIM disease related human protein variantsMemPype: a pipeline for the annotation of eukaryotic membrane proteins.TPpred2: improving the prediction of mitochondrial targeting peptide cleavage sites by exploiting sequence motifs.TPpred3 detects and discriminates mitochondrial and chloroplastic targeting peptides in eukaryotic proteins.Prediction of disulfide connectivity in proteins with machine-learning methods and correlated mutations.eDGAR: a database of Disease-Gene Associations with annotated Relationships among genesINPS-MD: a web server to predict stability of protein variants from sequence and structure.Computer-based prediction of mitochondria-targeting peptides.SChloro: directing Viridiplantae proteins to six chloroplastic sub-compartments.Grammatical-Restrained Hidden Conditional Random Fields for Bioinformatics applicationsThe prediction of organelle-targeting peptides in eukaryotic proteins with Grammatical-Restrained Hidden Conditional Random Fields.ISPRED4: interaction sites PREDiction in protein structures with a refining grammar model.Improving the prediction of disulfide bonds in Eukaryotes with machine learning methods and protein subcellular localization.DeepSig: deep learning improves signal peptide detection in proteins.BUSCA: an integrative web server to predict subcellular localization of proteins.Machine-Learning Methods to Predict Protein Interaction Sites in Folded ProteinsPrediction of the Bonding State of Cysteine Residues in Proteins with Machine-Learning MethodsOn the biases in predictions of protein stability changes upon variations: the INPS test caseFunctional and Structural Features of Disease-Related Protein Variants.Performance of computational methods for the evaluation of pericentriolar material 1 missense variants in CAGI-5Assessment of blind predictions of the clinical significance of BRCA1 and BRCA2 variantsAre machine learning based methods suited to address complex biological problems? Lessons from CAGI-5 challengesAssessing predictions of the impact of variants on splicing in CAGI5Assessing computational predictions of the phenotypic effect of cystathionine-beta-synthase variantsAssessment of predicted enzymatic activity of α-N-acetylglucosaminidase variants of unknown significance for CAGI 2016Assessment of methods for predicting the effects of PTEN and TPMT protein variantsEvaluating the predictions of the protein stability change upon single amino acid substitutions for the FXN CAGI5 challengeDeepMito: accurate prediction of protein sub-mitochondrial localization using convolutional neural networks
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description
onderzoeker
@nl
researcher
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հետազոտող
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name
Castrense Savojardo
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Castrense Savojardo
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Castrense Savojardo
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Castrense Savojardo
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type
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Castrense Savojardo
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Castrense Savojardo
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Castrense Savojardo
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Castrense Savojardo
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Castrense Savojardo
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Castrense Savojardo
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Castrense Savojardo
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Castrense Savojardo
@nl
P106
P1153
35189582500
P2456
P31
P496
0000-0002-7359-0633