scholarly journals Prediction of function for the polyprenyl transferase subgroup in the isoprenoid synthase superfamily

2013 ◽  
Vol 110 (13) ◽  
pp. E1196-E1202 ◽  
Author(s):  
F. H. Wallrapp ◽  
J.-J. Pan ◽  
G. Ramamoorthy ◽  
D. E. Almonacid ◽  
B. S. Hillerich ◽  
...  
Keyword(s):  
Prediction Of Function

scholarly journals The ortholog conjecture revisited: the value of orthologs and paralogs in function prediction

2020 ◽  
Vol 36 (Supplement_1) ◽  
pp. i219-i226 ◽  
Author(s):  
Moses Stamboulian ◽  
Rafael F Guerrero ◽  
Matthew W Hahn ◽  
Predrag Radivojac
Keyword(s):  
Prediction Accuracy ◽  
Homo Sapiens ◽  
Computational Prediction ◽  
Function Prediction ◽  
Supplementary Information ◽  
Orthologous Genes ◽  
Homologous Genes ◽  
Cast Doubt ◽  
Prediction Of Function ◽  
Function Transfer

Abstract Motivation The computational prediction of gene function is a key step in making full use of newly sequenced genomes. Function is generally predicted by transferring annotations from homologous genes or proteins for which experimental evidence exists. The ‘ortholog conjecture’ proposes that orthologous genes should be preferred when making such predictions, as they evolve functions more slowly than paralogous genes. Previous research has provided little support for the ortholog conjecture, though the incomplete nature of the data cast doubt on the conclusions. Results We use experimental annotations from over 40 000 proteins, drawn from over 80 000 publications, to revisit the ortholog conjecture in two pairs of species: (i) Homo sapiens and Mus musculus and (ii) Saccharomyces cerevisiae and Schizosaccharomyces pombe. By making a distinction between questions about the evolution of function versus questions about the prediction of function, we find strong evidence against the ortholog conjecture in the context of function prediction, though questions about the evolution of function remain difficult to address. In both pairs of species, we quantify the amount of information that would be ignored if paralogs are discarded, as well as the resulting loss in prediction accuracy. Taken as a whole, our results support the view that the types of homologs used for function transfer are largely irrelevant to the task of function prediction. Maximizing the amount of data used for this task, regardless of whether it comes from orthologs or paralogs, is most likely to lead to higher prediction accuracy. Availability and implementation https://github.com/predragradivojac/oc. Supplementary information Supplementary data are available at Bioinformatics online.

Role of Electrostatic Interactions for the Prediction of Function and Specificity in Redox Protein-protein Interactions

2020 ◽  
Vol 159 ◽  
pp. S24
Author(s):  
Md Faruq Hossain ◽  
Yana Bodnar ◽  
Volkmar Liebscher ◽  
Manuela Gellert ◽  
Christopher Horst Lillig
Keyword(s):  
Protein Interactions ◽  
Electrostatic Interactions ◽  
Protein Protein Interactions ◽  
Redox Protein ◽  
Prediction Of Function

scholarly journals Prediction of function after stroke: a critical review.

Stroke ◽  
1986 ◽  
Vol 17 (4) ◽  
pp. 765-776 ◽  
Author(s):  
L Jongbloed
Keyword(s):  
Critical Review ◽  
Prediction Of Function

scholarly journals Whole-Genome Sequence of Stenotrophomonas maltophilia ZBG7B Reveals Its Biotechnological Potential

2015 ◽  
Vol 3 (6) ◽  
Author(s):  
Kok-Gan Chan ◽  
Teik-Min Chong ◽  
Tan-Guan-Sheng Adrian ◽  
Heng Leong Kher ◽  
Kar-Wai Hong ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Bacterial Strain ◽  
Stenotrophomonas Maltophilia ◽  
Draft Genome ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Biotechnological Potential ◽  
Vineyard Soil ◽  
Genes Encoding ◽  
Prediction Of Function

Stenotrophomonas maltophilia ZBG7B was isolated from vineyard soil of Zellenberg, France. Here, we present the draft genome sequence of this bacterial strain, which has facilitated the prediction of function for several genes encoding biotechnologically important enzymes, such as xylosidase, xylanase, laccase, and chitinase.

scholarly journals Prediction of Function in ABCA4-Related Retinopathy Using Ensemble Machine Learning

2020 ◽  
Vol 9 (8) ◽  
pp. 2428 ◽  
Author(s):  
Philipp L. Müller ◽  
Tim Treis ◽  
Alexandru Odainic ◽  
Maximilian Pfau ◽  
Philipp Herrmann ◽  
...  
Keyword(s):  
Machine Learning ◽  
Visual Impairment ◽  
Age Of Onset ◽  
Outer Nuclear Layer ◽  
Stargardt Disease ◽  
Full Field ◽  
Corrected Visual Acuity ◽  
Ensemble Machine Learning ◽  
Prediction Of Function ◽  
Patient Burden

Full-field electroretinogram (ERG) and best corrected visual acuity (BCVA) measures have been shown to have prognostic value for recessive Stargardt disease (also called “ABCA4-related retinopathy”). These functional tests may serve as a performance-outcome-measure (PerfO) in emerging interventional clinical trials, but utility is limited by variability and patient burden. To address these limitations, an ensemble machine-learning-based approach was evaluated to differentiate patients from controls, and predict disease categories depending on ERG (‘inferred ERG’) and visual impairment (‘inferred visual impairment’) as well as BCVA values (‘inferred BCVA’) based on microstructural imaging (utilizing spectral-domain optical coherence tomography) and patient data. The accuracy for ‘inferred ERG’ and ‘inferred visual impairment’ was up to 99.53 ± 1.02%. Prediction of BCVA values (‘inferred BCVA’) achieved a precision of ±0.3LogMAR in up to 85.31% of eyes. Analysis of the permutation importance revealed that foveal status was the most important feature for BCVA prediction, while the thickness of outer nuclear layer and photoreceptor inner and outer segments as well as age of onset highly ranked for all predictions. ‘Inferred ERG’, ‘inferred visual impairment’, and ‘inferred BCVA’, herein, represent accurate estimates of differential functional effects of retinal microstructure, and offer quasi-functional parameters with the potential for a refined patient assessment, and investigation of potential future treatment effects or disease progression.

Prediction of function of preserved kidneys by lactate dehydrogenase isoenzyme levels

Cryobiology ◽  
1975 ◽  
Vol 12 (6) ◽  
pp. 576
Author(s):  
J.F.B. Lockwood ◽  
R.A. Ulan ◽  
C.R. Stiller ◽  
A.R. Henderson
Keyword(s):  
Lactate Dehydrogenase ◽  
Dehydrogenase Isoenzyme ◽  
Prediction Of Function
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