Robust artificial neural networks and outlier detection. Technical report

Large outliers break down linear and nonlinear regression models. Robust regression methods allow one to filter out the outliers when building a model. By replacing the traditional least squares criterion with the least trimmed squares criterion, in which half of data is treated as potential outliers, one can fit accurate regression models to strongly contaminated data. High-breakdown methods have become very well established in linear regression, but have started being applied for non-linear regression only recently. In this work, we examine the problem of fitting artificial neural networks to contaminated data using least trimmed squares criterion. We introduce a penalized least trimmed squares criterion which prevents unnecessary removal of valid data. Training of ANNs leads to a challenging non-smooth global optimization problem. We compare the efficiency of several derivative-free optimization methods in solving it, and show that our approach identifies the outliers correctly when ANNs are used for nonlinear regression

Analysis of defect related optical transitions in biased AlGaN/GaN heterostructures

The optical transitions in AlGaN/GaN heterostructures that are grown by metalorganic chemical vapor deposition (MOCVD) have been investigated in detail by using Hall and room temperature (RT) photoluminescence (PL) measurements. The Hall measurements show that there is two-dimensional electron gas (2DEG) conduction at the AlGaN/GaN heterointerface. PL measurements show that in addition to the characteristic near-band edge (BE) transition, there are blue (BL) and yellow luminescence (YL) bands, free-exciton transition (FE), and a neighboring emission band (NEB). To analyze these transitions in detail, the PL measurements were taken under bias where the applied electric field changed from 0 to 50 V/cm. Due to the applied electric field, band bending occurs and NEB separates into two different peaks as an ultraviolet luminescence (UVL) and Y4 band. Among these bands, only the yellow band is unaffected with the applied electric field. The luminescence intensity change of these bands with an electric field is investigated in detail. As a result, the most probable candidate of the intensity decrease with an increasing electric field is the reduction in the radiative lifetime. © 2010 Elsevier Ltd. All rights reserved

Electrical Properties of the Layered Single Crystals TlGaSe2 and TlInS2

In the doped crystals TlGaSe2 and TlInS2, using method of temperature dependencies of DC resistance in the temperature range of 100 – 300 K, the phase transitions at the temperatures of 240 – 245 K and 105 – 120 K were observed. The AC conductance measurements at room temperature indicated the hopping mechanism of carrier transport in the studied samples

ISSR Analysis of Variability of Cultivated Form and Varieties of Pomegranate (Punica granatum L.) from Azerbaijan

The article presents the results of a study of genetic polymorphism for the first time carried out on pomegranate varieties and forms of Azerbaijan origin using molecular markers. In total, 102 PCR fragments were identified, of which 80 were polymorphic. The high level of polymorphism (75.5%) and the rich genetic diversity were identified among the studied pomegranate collection. As a result of data analysis and on the basis of the values of the basic parameters (PIC, EMR, MI, RP, MRP) determining informativeness of markers, all 14 ISSR primers were suitable for genotyping pomegranate accessions. The most effective markers (UBC808, UBC811, UBC834, and UBC840) were identified among the set of primers tested. A dendrogram was constructed on the basis of the data obtained, which made it possible to group genotypes into 16 major clusters. The genetic similarity index ranged from 0.032 to 0.94. The study of the genetic relationship of different pomegranate varieties confirms the effectiveness of the ISSR method, which makes it possible to determine the level of genetic diversity, as well as to establish the relationship among the studied pomegranate accessions

Extracellular matrix mimetic peptide scaffolds for neural stem cell culture and differentiation

Self-assembled peptide nanofibers form three-dimensional networks that are quite similar to fibrous extracellular matrix (ECM) in their physical structure. By incorporating short peptide sequences derived from ECM proteins, these nanofibers provide bioactive platforms for cell culture studies. This protocol provides information about preparation and characterization of self-assembled peptide nanofiber scaffolds, culturing of neural stem cells (NSCs) on these scaffolds, and analysis of cell behavior. As cell behavior analyses, viability and proliferation of NSCs as well as investigation of differentiation by immunocytochemistry, qRT-PCR, western blot, and morphological analysis on ECM mimetic peptide nanofiber scaffolds are described

A new scoring system in Cystic Fibrosis: statistical tools for database analysis – a preliminary report

<p>Abstract</p> <p>Background</p> <p>Cystic fibrosis is the most common fatal genetic disorder in the Caucasian population. Scoring systems for assessment of Cystic fibrosis disease severity have been used for almost 50 years, without being adapted to the milder phenotype of the disease in the 21^stcentury. The aim of this current project is to develop a new scoring system using a database and employing various statistical tools. This study protocol reports the development of the statistical tools in order to create such a scoring system.</p> <p>Methods</p> <p>The evaluation is based on the Cystic Fibrosis database from the cohort at the Royal Children's Hospital in Melbourne. Initially, unsupervised clustering of the all data records was performed using a range of clustering algorithms. In particular incremental clustering algorithms were used. The clusters obtained were characterised using rules from decision trees and the results examined by clinicians. In order to obtain a clearer definition of classes expert opinion of each individual's clinical severity was sought. After data preparation including expert-opinion of an individual's clinical severity on a 3 point-scale (mild, moderate and severe disease), two multivariate techniques were used throughout the analysis to establish a method that would have a better success in feature selection and model derivation: 'Canonical Analysis of Principal Coordinates' and 'Linear Discriminant Analysis'. A 3-step procedure was performed with (1) selection of features, (2) extracting 5 severity classes out of a 3 severity class as defined per expert-opinion and (3) establishment of calibration datasets.</p> <p>Results</p> <p>(1) Feature selection: CAP has a more effective "modelling" focus than DA.</p> <p>(2) Extraction of 5 severity classes: after variables were identified as important in discriminating contiguous CF severity groups on the 3-point scale as mild/moderate and moderate/severe, Discriminant Function (DF) was used to determine the new groups mild, intermediate moderate, moderate, intermediate severe and severe disease. (3) Generated confusion tables showed a misclassification rate of 19.1% for males and 16.5% for females, with a majority of misallocations into adjacent severity classes particularly for males.</p> <p>Conclusion</p> <p>Our preliminary data show that using CAP for detection of selection features and Linear DA to derive the actual model in a CF database might be helpful in developing a scoring system. However, there are several limitations, particularly more data entry points are needed to finalize a score and the statistical tools have further to be refined and validated, with re-running the statistical methods in the larger dataset.</p

Coding SNPs analysis highlights genetic relationships and evolution pattern in eggplant complexes

[EN] Brinjal (Solanum melongena), scarlet (S. aethiopicum) and gboma (S. macrocarpon) eggplants are three Old World domesticates. The genomic DNA of a collection of accessions belonging to the three cultivated species, along with a representation of various wild relatives, was characterized for the presence of single nucleotide polymorphisms (SNPs) using a genotype-by-sequencing approach. A total of 210 million useful reads were produced and were successfully aligned to the reference eggplant genome sequence. Out of the 75,399 polymorphic sites identified among the 76 entries in study, 12,859 were associated with coding sequence. A genetic relationships analysis, supported by the output of the FastSTRUCTURE software, identified four major sub-groups as present in the germplasm panel. The first of these clustered S. aethiopicum with its wild ancestor S. anguivi; the second, S. melongena, its wild progenitor S. insanum, and its relatives S. incanum, S. lichtensteinii and S. linneanum; the third, S. macrocarpon and its wild ancestor S. dasyphyllum; and the fourth, the New World species S. sisymbriifolium, S. torvum and S. elaeagnifolium. By applying a hierarchical FastSTRUCTURE analysis on partitioned data, it was also possible to resolve the ambiguous membership of the accessions of S. campylacanthum, S. violaceum, S. lidii, S. vespertilio and S. tomentsum, as well as to genetically differentiate the three species of New World Origin. A principal coordinates analysis performed both on the entire germplasm panel and also separately on the entries belonging to sub-groups revealed a clear separation among species, although not between each of the domesticates and their respective wild ancestors. There was no clear differentiation between either distinct cultivar groups or different geographical provenance. Adopting various approaches to analyze SNP variation provided support for interpretation of results. The genotyping-by-sequencing approach showed to be highly efficient for both quantifying genetic diversity and establishing genetic relationships among and within cultivated eggplants and their wild relatives. The relevance of these results to the evolution of eggplants, as well as to their genetic improvement, is discussed.This work has been funded in part by European Unions Horizon 2020 Research and Innovation Programme under grant agreement No 677379 (G2P-SOL project: Linking genetic resources, genomes and phenotypes of Solanaceous crops) and by Spanish Ministerio de Economia, Industria y Competitividad and Fondo Europeo de Desarrollo Regional (grant AGL2015-64755-R from MINECO/FEDER). Funding has also been received from the initiative "Adapting Agriculture to Climate Change: Collecting, Protecting and Preparing Crop Wild Relatives", which is supported by the Government of Norway. This last project is managed by the Global Crop Diversity Trust with the Millennium Seed Bank of the Royal Botanic Gardens, Kew and implemented in partnership with national and international gene banks and plant breeding institutes around the world. For further information see the project website:http://www.cwrdiversity.org/. Pietro Gramazio is grateful to Universitat Politecnica de Valencia for a pre-doctoral (Programa FPI de la UPV-Subprograma 1/2013 call) contract. Mariola Plazas is grateful to Spanish Ministerio de Economia, Industria y Competitividad for a post-doctoral grant within the Santiago Grisolia Programme (FCJI-2015-24835). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Acquadro, A.; Barchi, L.; Gramazio, P.; Portis, E.; Vilanova Navarro, S.; Comino, C.; Plazas Ávila, MDLO.... (2017). Coding SNPs analysis highlights genetic relationships and evolution pattern in eggplant complexes. PLoS ONE. 12(7). https://doi.org/10.1371/journal.pone.0180774Se018077412

An eQTL Analysis of Partial Resistance to Puccinia hordei in Barley

Background - Genetic resistance to barley leaf rust caused by Puccinia hordei involves both R genes and quantitative trait loci. The R genes provide higher but less durable resistance than the quantitative trait loci. Consequently, exploring quantitative or partial resistance has become a favorable alternative for controlling disease. Four quantitative trait loci for partial resistance to leaf rust have been identified in the doubled haploid Steptoe (St)/Morex (Mx) mapping population. Further investigations are required to study the molecular mechanisms underpinning partial resistance and ultimately identify the causal genes.Methodology/Principal Findings - We explored partial resistance to barley leaf rust using a genetical genomics approach. We recorded RNA transcript abundance corresponding to each probe on a 15K Agilent custom barley microarray in seedlings from St and Mx and 144 doubled haploid lines of the St/Mx population. A total of 1154 and 1037 genes were, respectively, identified as being P. hordei-responsive among the St and Mx and differentially expressed between P. hordei-infected St and Mx. Normalized ratios from 72 distant-pair hybridisations were used to map the genetic determinants of variation in transcript abundance by expression quantitative trait locus (eQTL) mapping generating 15685 eQTL from 9557 genes. Correlation analysis identified 128 genes that were correlated with resistance, of which 89 had eQTL co-locating with the phenotypic quantitative trait loci (pQTL). Transcript abundance in the parents and conservation of synteny with rice allowed us to prioritise six genes as candidates for Rphq11, the pQTL of largest effect, and highlight one, a phospholipid hydroperoxide glutathione peroxidase (HvPHGPx) for detailed analysis.Conclusions/Significance - The eQTL approach yielded information that led to the identification of strong candidate genes underlying pQTL for resistance to leaf rust in barley and on the general pathogen response pathway. The dataset will facilitate a systems appraisal of this host-pathogen interaction and, potentially, for other traits measured in this populatio