An entropy based heuristic model for predicting functional sub-type divisions of protein families

Multiple sequence alignments of protein families are often used for locating residues that are widely apart in the sequence, which are considered as influential for determining functional specificity of proteins towards various substrates, ligands, DNA and other proteins. In this paper, we propose an entropy-score based heuristic algorithm model for predicting functional sub-family divisions of protein families, given the multiple sequence alignment of the protein family as input without any functional sub-type or key site information given for any protein sequence. Two of the experimented test-cases are reported in this paper. First test-case is Nucleotidyl Cyclase protein family consisting of guanalyate and adenylate cyclases. And the second test-case is a dataset of proteins taken from six superfamilies in Structure-Function Linkage Database (SFLD). Results from these test-cases are reported in terms of confirmed sub-type divisions with phylogeny relations from former studies in the literature

Optimization of morphological data in numerical taxonomy analysis using genetic algorithms feature selection method

Studies in Numerical Taxonomy are carried out by measuring characters as much as possible. The workload over scientists and labor to perform measurements will increase proportionally with the number of variables (or characters) to be used in the study. However, some part of the data may be irrelevant or sometimes meaningless. Here in this study, we introduce an algorithm to obtain a subset of data with minimum characters that can represent original data. Morphological characters were used in optimization of data by Genetic Algorithms Feature Selection method. The analyses were performed on an 18 character*11 taxa data matrix with standardized continuous characters. The analyses resulted in a minimum set of 2 characters, which means the original tree based on the complete data can also be constructed by those two characters

Testing robustness of relative complexity measure method constructing robust phylogenetic trees for Galanthus L. Using the relative complexity measure

Background: Most phylogeny analysis methods based on molecular sequences use multiple alignment where the quality of the alignment, which is dependent on the alignment parameters, determines the accuracy of the resulting trees. Different parameter combinations chosen for the multiple alignment may result in different phylogenies. A new non-alignment based approach, Relative Complexity Measure (RCM), has been introduced to tackle this problem and proven to work in fungi and mitochondrial DNA. Result: In this work, we present an application of the RCM method to reconstruct robust phylogenetic trees using sequence data for genus Galanthus obtained from different regions in Turkey. Phylogenies have been analyzed using nuclear and chloroplast DNA sequences. Results showed that, the tree obtained from nuclear ribosomal RNA gene sequences was more robust, while the tree obtained from the chloroplast DNA showed a higher degree of variation. Conclusions: Phylogenies generated by Relative Complexity Measure were found to be robust and results of RCM were more reliable than the compared techniques. Particularly, to overcome MSA-based problems, RCM seems to be a reasonable way and a good alternative to MSA-based phylogenetic analysis. We believe our method will become a mainstream phylogeny construction method especially for the highly variable sequence families where the accuracy of the MSA heavily depends on the alignment parameters

Toward a Flexible Metadata Pipeline for Fish Specimen Images

Flexible metadata pipelines are crucial for supporting the FAIR data principles. Despite this need, researchers seldom report their approaches for identifying metadata standards and protocols that support optimal flexibility. This paper reports on an initiative targeting the development of a flexible metadata pipeline for a collection containing over 300,000 digital fish specimen images, harvested from multiple data repositories and fish collections. The images and their associated metadata are being used for AI-related scientific research involving automated species identification, segmentation and trait extraction. The paper provides contextual background, followed by the presentation of a four-phased approach involving: 1. Assessment of the Problem, 2. Investigation of Solutions, 3. Implementation, and 4. Refinement. The work is part of the NSF Harnessing the Data Revolution, Biology Guided Neural Networks (NSF/HDR-BGNN) project and the HDR Imageomics Institute. An RDF graph prototype pipeline is presented, followed by a discussion of research implications and conclusion summarizing the results.Comment: 12 pages. 5 figures. Presented at the 16th International Conference on Metadata and Semantics Research. To be published in the conference proceedings of Metadata and Semantic Research: 16th International Conference, MTSR 2022, London, United Kingdom, November 8-10, 202

Testing robustness of relative complexity measure method constructing robust phylogenetic trees for \u3ci\u3eGalanthus\u3c/i\u3e L. Using the relative complexity measure

Background: Most phylogeny analysis methods based on molecular sequences use multiple alignment where the quality of the alignment, which is dependent on the alignment parameters, determines the accuracy of the resulting trees. Different parameter combinations chosen for the multiple alignment may result in different phylogenies. A new non-alignment based approach, Relative Complexity Measure (RCM), has been introduced to tackle this problem and proven to work in fungi and mitochondrial DNA. Result: In this work, we present an application of the RCM method to reconstruct robust phylogenetic trees using sequence data for genus Galanthus obtained from different regions in Turkey. Phylogenies have been analyzed using nuclear and chloroplast DNA sequences. Results showed that, the tree obtained from nuclear ribosomal RNA gene sequences was more robust, while the tree obtained from the chloroplast DNA showed a higher degree of variation. Conclusions: Phylogenies generated by Relative Complexity Measure were found to be robust and results of RCM were more reliable than the compared techniques. Particularly, to overcome MSA-based problems, RCM seems to be a reasonable way and a good alternative to MSA-based phylogenetic analysis. We believe our method will become a mainstream phylogeny construction method especially for the highly variable sequence families where the accuracy of the MSA heavily depends on the alignment parameters

High Epstein-Barr Virus Load and Genomic Diversity Are Associated with Generation of gp350-Specific Neutralizing Antibodies following Acute Infectious Mononucleosis

The Epstein-Barr virus (EBV) gp350 glycoprotein interacts with the cellular receptor to mediate viral entry and is thought to be the major target for neutralizing antibodies. To better understand the role of EBV-specific antibodies in the control of viral replication and the evolution of sequence diversity, we measured EBV gp350-specific antibody responses and sequenced the gp350 gene in samples obtained from individuals experiencing primary EBV infection (acute infectious mononucleosis [AIM]) and again 6 months later (during convalescence [CONV]). EBV gp350-specific IgG was detected in the sera of 17 (71%) of 24 individuals at the time of AIM and all 24 (100%) individuals during CONV; binding antibody titers increased from AIM through CONV, reaching levels equivalent to those in age-matched, chronically infected individuals. Antibody-dependent cell-mediated phagocytosis (ADCP) was rarely detected during AIM (4 of 24 individuals; 17%) but was commonly detected during CONV (19 of 24 individuals; 79%). The majority (83%) of samples taken during AIM neutralized infection of primary B cells; all samples obtained at 6 months postdiagnosis neutralized EBV infection of cultured and primary target cells. Deep sequencing revealed interpatient gp350 sequence variation but conservation of the CR2-binding site. The levels of gp350-specific neutralizing activity directly correlated with higher peripheral blood EBV DNA levels during AIM and a greater evolution of diversity in gp350 nucleotide sequences from AIM to CONV. In summary, we conclude that the viral load and EBV gp350 diversity during early infection are associated with the development of neutralizing antibody responses following AIM. IMPORTANCE: Antibodies against viral surface proteins can blunt the spread of viral infection by coating viral particles, mediating uptake by immune cells, or blocking interaction with host cell receptors, making them a desirable component of a sterilizing vaccine. The EBV surface protein gp350 is a major target for antibodies. We report the detection of EBV gp350-specific antibodies capable of neutralizing EBV infection in vitro The majority of gp350-directed vaccines focus on glycoproteins from lab-adapted strains, which may poorly reflect primary viral envelope diversity. We report some of the first primary gp350 sequences, noting that the gp350 host receptor binding site is remarkably stable across patients and time. However, changes in overall gene diversity were detectable during infection. Patients with higher peripheral blood viral loads in primary infection and greater changes in viral diversity generated more efficient antibodies. Our findings provide insight into the generation of functional antibodies, necessary for vaccine development

Testing robustness of relative complexity measure method constructing robust phylogenetic trees for \u3ci\u3eGalanthus\u3c/i\u3e L. Using the relative complexity measure

Background: Most phylogeny analysis methods based on molecular sequences use multiple alignment where the quality of the alignment, which is dependent on the alignment parameters, determines the accuracy of the resulting trees. Different parameter combinations chosen for the multiple alignment may result in different phylogenies. A new non-alignment based approach, Relative Complexity Measure (RCM), has been introduced to tackle this problem and proven to work in fungi and mitochondrial DNA. Result: In this work, we present an application of the RCM method to reconstruct robust phylogenetic trees using sequence data for genus Galanthus obtained from different regions in Turkey. Phylogenies have been analyzed using nuclear and chloroplast DNA sequences. Results showed that, the tree obtained from nuclear ribosomal RNA gene sequences was more robust, while the tree obtained from the chloroplast DNA showed a higher degree of variation. Conclusions: Phylogenies generated by Relative Complexity Measure were found to be robust and results of RCM were more reliable than the compared techniques. Particularly, to overcome MSA-based problems, RCM seems to be a reasonable way and a good alternative to MSA-based phylogenetic analysis. We believe our method will become a mainstream phylogeny construction method especially for the highly variable sequence families where the accuracy of the MSA heavily depends on the alignment parameters

Testing robustness of relative complexity measure method constructing robust phylogenetic trees for Galanthus L. Using the relative complexity measure

Background: Most phylogeny analysis methods based on molecular sequences use multiple alignment where the quality of the alignment, which is dependent on the alignment parameters, determines the accuracy of the resulting trees. Different parameter combinations chosen for the multiple alignment may result in different phylogenies. A new non-alignment based approach, Relative Complexity Measure (RCM), has been introduced to tackle this problem and proven to work in fungi and mitochondrial DNA