scholarly journals Surface Map Homology Inference

2021 ◽  
Vol 40 (5) ◽  
pp. 193-203
Author(s):  
J. Born ◽  
P. Schmidt ◽  
M. Campen ◽  
L. Kobbelt
Keyword(s):  
Homology Inference

scholarly journals Evaluation of BLAST-based edge-weighting metrics used for homology inference with the Markov Clustering algorithm

2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Theodore R. Gibbons ◽  
Stephen M. Mount ◽  
Endymion D. Cooper ◽  
Charles F. Delwiche
Keyword(s):  
Clustering Algorithm ◽  
Edge Weighting ◽  
Homology Inference ◽  
Markov Clustering

scholarly journals A mass spectrometry guided approach for the identification of novel vaccine candidates in gram-negative pathogens

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Daniel Hornburg ◽  
Tobias Kruse ◽  
Florian Anderl ◽  
Christina Daschkin ◽  
Raphaela P. Semper ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Model Organism ◽  
Antibody Responses ◽  
Surface Proteins ◽  
Gram Negative ◽  
Vaccine Candidates ◽  
Bacterial Proteins ◽  
Computational Homology ◽  
Cell Responses ◽  
Homology Inference

AbstractVaccination is the most effective method to prevent infectious diseases. However, approaches to identify novel vaccine candidates are commonly laborious and protracted. While surface proteins are suitable vaccine candidates and can elicit antibacterial antibody responses, systematic approaches to define surfomes from gram-negatives have rarely been successful. Here we developed a combined discovery-driven mass spectrometry and computational strategy to identify bacterial vaccine candidates and validate their immunogenicity using a highly prevalent gram-negative pathogen, Helicobacter pylori, as a model organism. We efficiently isolated surface antigens by enzymatic cleavage, with a design of experiment based strategy to experimentally dissect cell surface-exposed from cytosolic proteins. From a total of 1,153 quantified bacterial proteins, we thereby identified 72 surface exposed antigens and further prioritized candidates by computational homology inference within and across species. We next tested candidate-specific immune responses. All candidates were recognized in sera from infected patients, and readily induced antibody responses after vaccination of mice. The candidate jhp_0775 induced specific B and T cell responses and significantly reduced colonization levels in mouse therapeutic vaccination studies. In infected humans, we further show that jhp_0775 is immunogenic and activates IFNγ secretion from peripheral CD4+ and CD8+ T cells. Our strategy provides a generic preclinical screening, selection and validation process for novel vaccine candidates against gram-negative bacteria, which could be employed to other gram-negative pathogens.

scholarly journals phylostratr: A framework for phylostratigraphy

2018 ◽  
Author(s):  
Zebulun Arendsee ◽  
Jing Li ◽  
Urminder Singh ◽  
Arun Seetharam ◽  
Karin Dorman ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Arabidopsis Thaliana ◽  
False Positive ◽  
Source Code ◽  
R Package ◽  
High Quality ◽  
Organelle Genomes ◽  
Alternative Algorithm ◽  
Homology Inference ◽  
Quality Assessments

AbstractMotivationThe goal of phylostratigraphy is to infer the evolutionary origin of each gene in an organism. Currently, there are no general pipelines for this task. We present an R package, phylostratr, to fill this gap, making high-quality phylostratigraphic analysis accessible to non-specialists.ResultsPhylostratigraphic analysis entails searching for homologs within increasingly broad clades. The highest clade that contains all homologs of a gene is that gene’s phylostratum. We have created a general R-based framework, phylostratr, for estimating the phylostratum of every gene in a species. The program can fully automate an analysis: select species for a balanced representation of each strata, retrieve the sequences from UniProt, build BLAST databases, run BLAST, infer homologs for each gene against each subject species, determine phylostrata, and return summaries and diagnostics. phylostratr allows extensive customization. A user may: modify the automatically-generated clade tree or use their own tree; provide custom sequences in place of those automatically retrieved from UniProt; replace BLAST with an alternative algorithm; or tailor the method and sensitivity of the homology inference classifier. phylostratr also offers proteome quality assessments, false-positive diagnostics, and checks for missing organelle genomes. We show the utility of phylostratr through case studies in Arabidopsis thaliana and Saccharomyces cerevisiae.Availabilityphylostratr source code and vignettes are available on GitHub at https://github.com/arendsee/[email protected]

scholarly journals Remote homology clustering identifies lowly conserved families of effector proteins in plant-pathogenic fungi

2021 ◽  
Vol 7 (9) ◽  
Author(s):  
Darcy A. B. Jones ◽  
Paula M. Moolhuijzen ◽  
James K. Hane
Keyword(s):  
Fungal Pathogens ◽  
Pathogenic Fungi ◽  
Comparison Method ◽  
Fungal Species ◽  
Effector Proteins ◽  
Plant Diseases ◽  
Plant Host ◽  
Homology Inference ◽  
Developing Area ◽  
Inference Methods

Plant diseases caused by fungal pathogens are typically initiated by molecular interactions between ‘effector’ molecules released by a pathogen and receptor molecules on or within the plant host cell. In many cases these effector-receptor interactions directly determine host resistance or susceptibility. The search for fungal effector proteins is a developing area in fungal-plant pathology, with more than 165 distinct confirmed fungal effector proteins in the public domain. For a small number of these, novel effectors can be rapidly discovered across multiple fungal species through the identification of known effector homologues. However, many have no detectable homology by standard sequence-based search methods. This study employs a novel comparison method (RemEff) that is capable of identifying protein families with greater sensitivity than traditional homology-inference methods, leveraging a growing pool of confirmed fungal effector data to enable the prediction of novel fungal effector candidates by protein family association. Resources relating to the RemEff method and data used in this study are available from https://figshare.com/projects/Effector_protein_remote_homology/87965.

scholarly journals Adaptive Metrics for Adaptive Samples

Algorithms ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 200
Author(s):  
Nicholas J. Cavanna ◽  
Donald R. Sheehy
Keyword(s):  
Euclidean Space ◽  
Surface Reconstruction ◽  
Critical Points ◽  
Adaptive Sampling ◽  
Local Feature ◽  
Distance Functions ◽  
Feature Size ◽  
Homology Inference ◽  
Definition Of ◽  
Local Feature Size

We generalize the local-feature size definition of adaptive sampling used in surface reconstruction to relate it to an alternative metric on Euclidean space. In the new metric, adaptive samples become uniform samples, making it simpler both to give adaptive sampling versions of homological inference results and to prove topological guarantees using the critical points theory of distance functions. This ultimately leads to an algorithm for homology inference from samples whose spacing depends on their distance to a discrete representation of the complement space.

scholarly journals Homology Inference Based on a Reconciliation Approach for the Comparative Genomics of Protozoa

2018 ◽  
Vol 14 ◽  
pp. 117693431878513
Author(s):  
Darueck A Campos ◽  
Elisa C Pereira ◽  
Rodrigo Jardim ◽  
Rafael RC Cuadrat ◽  
Juliana S Bernardes ◽  
...  
Keyword(s):  
Comparative Genomics ◽  
Homology Inference

scholarly journals Zigzag Zoology: Rips Zigzags for Homology Inference

2014 ◽  
Vol 15 (5) ◽  
pp. 1151-1186 ◽  
Author(s):  
Steve Y. Oudot ◽  
Donald R. Sheehy
Keyword(s):  
Homology Inference
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