bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical investigation of non-perturbative kinetic effects of energetic particles on toroidicity-induced Alfvén eigenmodes in tokamaks and stellarators
Authors: Slaby Christoph , Könies Axel , Kleiber Ralf
Published: September 2016

The resonant interaction of shear Alfvén waves with energetic particles is investigated numerically in tokamak and stellarator geometry using a non-perturbative MHD-kinetic hybrid approach. The focus lies on toroidicity-induced Alfvén eigenmodes (TAEs), which are most easily destabilized by a fast-particle population in fusion plasmas. While the background plasma is treated within the framework of an ideal-MHD theory, the drive of the fast particles, as well as Landau damping of the background plasma, is modelled using the drift-kinetic Vlasov equation without collisions. Building on analytical theory, a fast numerical tool, STAE-K, has been developed to solve the resulting eigenvalue problem using a Riccati shooting method. The code, which can be used for parameter scans, is applied to tokamaks and the stellarator Wendelstein 7-X. High energetic-ion pressure leads to large growth rates of the TAEs and to their conversion into kinetically modified TAEs and kinetic Alfvén waves via continuum interaction. To better understand the physics of this conversion mechanism, the connections between TAEs and the shear Alfvén wave continuum are examined. It is shown that, when energetic particles are present, the continuum deforms substantially and the TAE frequency can leave the continuum gap. The interaction of the TAE with the continuum leads to singularities in the eigenfunctions. To further advance the physical model and also to eliminate the MHD continuum together with the singularities in the eigenfunctions, a fourth-order term connected to radiative damping has been included. The radiative damping term is connected to non-ideal effects of the bulk plasma and introduces higher-order derivatives to the model. Thus, it has the potential to substantially change the nature of the solution. For the first time, the fast-particle drive, Landau damping, continuum damping, and radiative damping have been modelled together in tokamak- as well as in stellarator geometry.
Diffusion and transport in locally disordered driven lattices
Authors: Wulf Thomas , Okupnik Alexander , Schmelcher Peter
Published: September 2016

We study the effect of disorder on the particle density evolution in a classical Hamiltonian driven lattice setup. If the disorder is localized within a finite sub-domain of the lattice, the emergence of strong tails in the density distribution which even increases towards larger positions is shown, thus yielding a highly non-Gaussian particle density evolution. As the key underlying mechanism, we identify the conversion between different components of the unperturbed systems mixed phase space which is induced by the disorder. Based on the introduction of individual conversion rates between chaotic and regular components, a theoretical model is developed which correctly predicts the scaling of the particle density. The effect of disorder on the transport properties is studied where a significant enhancement of the transport for cases of localized disorder is shown, thereby contrasting strongly the merely weak modification of the transport for global disorder.
Time-dependent density functional theory (TD-DFT) coupled with reference interaction site model self-consistent field explicitly including spatial electron density distribution (RISM-SCF-SEDD)
Authors: Yokogawa D.
Published: September 2016

Theoretical approach to design bright bio-imaging molecules is one of the most progressing ones. However, because of the system size and computational accuracy, the number of theoretical studies is limited to our knowledge. To overcome the difficulties, we developed a new method based on reference interaction site model self-consistent field explicitly including spatial electron density distribution and time-dependent density functional theory. We applied it to the calculation of indole and 5-cyanoindole at ground and excited states in gas and solution phases. The changes in the optimized geometries were clearly explained with resonance structures and the Stokes shift was correctly reproduced.
Recovering hidden dynamical modes from the generalized Langevin equation
Authors: Kawai Shinnosuke , Miyazaki Yusuke
Published: September 2016

In studying large molecular systems, insights can better be extracted by selecting a limited number of physical quantities for analysis rather than treating every atomic coordinate in detail. Some information may, however, be lost by projecting the total system onto a small number of coordinates. For such problems, the generalized Langevin equation (GLE) is shown to provide a useful framework to examine the interaction between the observed variables and their environment. Starting with the GLE obtained from the time series of the observed quantity, we perform a transformation to introduce a set of variables that describe dynamical modes existing in the environment. The introduced variables are shown to effectively recover the essential information of the total system that appeared to be lost by the projection.
Rate independence of material properties and remnant state variables during domain switching by electric field or stress in ferroelectric ceramics at room and high temperatures
Authors: Ji Dae Won , Kim Sang-Joo
Published: September 2016

Various numbers of electric field or compressive stress pulses with increasing magnitude are applied to a poled lead titanate zirconate rectangular parallelepiped specimen. Changes in linear material properties are estimated from measured responses and plotted versus remnant polarization. The dependence of linear material properties on remnant polarization is shown to be the same independent of the overall rate of domain switching by electric field or stress at room and high temperatures. The evolution path of remnant polarization and strains in the plane of remnant state variables is also found to be equal independent of switching rate at room and high temperatures. Finally, when the values of remnant state variables at high temperature are transformed to those of reference remnant state variables, the evolution path of the reference remnant state variables is compared to be coincident with that of remnant state variables at room temperature, implying the same switching process at different temperatures.
Lengthscale effects on exchange coupling in Co-Pt L1 + L12 nanochessboards
Authors: Vetter Eric P. , Geng Liwei , Ghatwai Priya , Gilbert Dustin A. , Jin Yongmei , Soffa William A. , Floro Jerrold A.
Published: September 2016

The Co-Pt nanochessboard is a quasi-periodic, nanocomposite tiling of L10 and L12 magnetic phases that offers a novel structure for the investigation of exchange coupling, relevant to permanent magnet applications. Periodicity of the tiling is controlled by the rate of cooling through the eutectoid isotherm, resulting in control over the L10-L12 exchange coupling. First order reversal curve analysis reveals a transition from partial coupling to nearly complete exchange-coupling in a Co40.2Pt59.8 nanochessboard structured alloy as the periodicity is reduced below the critical correlation length. Micromagnetic simulations give insights into how exchange coupling manifests in the tiling, and its impact on microscopic magnetization reversal mechanisms.
International Physics Olympiad held in Zürich
Authors: Feder Toni
Published: September 2016

Students convene in Einstein’s college town for fun and physics.
The graphene–semiconductor Schottky junction
Authors: Li Xinming , Zhu Hongwei
Published: September 2016

When a two-dimensional material abuts a three-dimensional one, a century-old electrical phenomenon finds new applicability.
Fluid instabilities that mimic animal growth
Authors: Bischofberger Irmgard , Nagel Sidney R.
Published: September 2016

In many biological systems, structures all grow at the same rate. That phenomenon of proportionate growth has now been observed in a nonequilibrium physical system.
Grazing winter and spring wheat crops improves the profitability of prime lamb production in mixed farming systems of Western Australia
Authors: Hussein E. , Thomas D. T. , Bell L. W. , Blache D.
Published: September 2016

Grazing immature cereal crops, particularly different varieties of wheat, has become widely adopted in the high rainfall areas of southern Australia. Recently, there has been growing interest in applying this technology in drier parts of the mixed farming zones of Western Australia. A modelling study was conducted to examine farm business returns with or without the grazing of immature wheat (winter and spring varieties) in different locations of Western Australia (Merredin, Wickepin and Kojonup), representing the low to high rainfall (319–528 mm) cropping regions, respectively. A combination of APSIM (crop simulation model) and GrassGro (pasture and livestock simulation model), were used to evaluate the changes in farm gross margins with the grazing of cereal crops at three locations of Western Australia. The results of the study showed that grazing the two wheat varieties (dual-purpose winter and spring) at the high rainfall location increased the profitability of the livestock enterprise by 2.5 times more than grazing crops at both low rainfall locations (P < 0.05). Across all years and sites, the average supplementary feeding costs were reduced by the inclusion of grazed winter (12%) and spring (2%) wheat crops in the lamb production system. The comparative reduction in the cost of supplementary feeding varied between locations and by crop variety within locations, due to both the frequency and average duration of the grazing of wheat crops in these regions, and the farm-stocking rate that was chosen. Both wheat varieties were grazed frequently at the lowest rainfall site (68% and 30% of years for winter and spring wheat varieties respectively), whereas grazing spring wheat was less frequent at the higher rainfall location and averaged 16% of years due to a greater difference in the relative availability of wheat crops versus pasture for grazing among regions. The grazing model assumed that there were abundant productive mixed ryegrass and subterranean clover pasture in the farming system. Overall, this study suggests that both winter and spring wheat crops are likely to supply green feed during the winter feed shortage (April–July) and reduce supplementary feed requirements for a short period of time in some seasons. The value of grazing crops is likely to be higher on farms with poorer soils and less productive pastures.
Enhanced use of phylogenetic data to inform public health approaches to HIV among men who have sex with men
Authors: German Danielle , Grabowski Mary Kate , Beyrer Chris
Published: September 2016

The multidimensional nature and continued evolution of HIV epidemics among men who have sex with men (MSM) requires innovative intervention approaches. Strategies are needed that recognise the individual, social and structural factors driving HIV transmission; that can pinpoint networks with heightened transmission risk; and that can help target intervention in real time. HIV phylogenetics is a rapidly evolving field with strong promise for informing innovative responses to the HIV epidemic among MSM. Currently, HIV phylogenetic insights are providing new understandings of characteristics of HIV epidemics involving MSM, social networks influencing transmission, characteristics of HIV transmission clusters involving MSM, targets for antiretroviral and other prevention strategies and dynamics of emergent epidemics. Maximising the potential of HIV phylogenetics for HIV responses among MSM will require attention to key methodological challenges and ethical considerations, as well as resolving key implementation and scientific questions. Enhanced and integrated use of HIV surveillance, sociobehavioural and phylogenetic data resources are becoming increasingly critical for informing public health approaches to HIV among MSM.
DNA and RNA topoisomerase activities of Top3β are promoted by mediator protein Tudor domain-containing protein 3
Authors: Siaw Grace Ee-Lu , Liu I-Fen , Lin Po-Yen , Been Michael D. , Hsieh Tao-shih
Published: September 2016

Significance

Tudor domain-containing protein 3 (TDRD3), a multidomain scaffold protein functions as an epigenetic reader on nuclear chromatin and binds with fragile X mental retardation protein on mRNA. It forms a conserved complex with topoisomerase 3β (Top3β), a type IA topoisomerase, and participates in both transcription and translation. The mechanism of how TDRD3 acts as Top3β’s partner in regulating these cellular processes is unknown. Here, we demonstrated that TDRD3 is able to stimulate Top3β’s DNA and RNA topoisomerase catalytic activities, through binding and stabilizing single-stranded regions in DNA and RNA substrates. Because these regions are the preferred site for Top3β, TDRD3 therefore acts as a regulator to provide access of the enzyme to these nucleic acid substrates and to act upon them.
Stability of the solution of stochastic differential equation driven by time-changed Lévy noise
Authors: Nane Erkan , Ni Yinan
Published: September 2016

This paper studies stabilities of the solution of stochastic differential equations (SDE) driven by time-changed Lévy noise in both probability and moment sense. This provides more flexibility in modeling schemes in application areas including physics, biology, engineering, finance and hydrology. Necessary conditions for the solution of time-changed SDE to be stable in different senses will be established. The connection between stability of the solution to time-changed SDE and that to corresponding original SDE will be disclosed. Examples related to different stabilities will be given. We study SDEs with time-changed Lévy noise, where the time-change processes are the inverse of general Lévy subordinators. These results are an important generalization of the results of Q. Wu (2016).
Roles for E-cadherin cell surface regulation in cancer
Authors: Petrova Yuliya I. , Schecterson Leslayann , Gumbiner Barry M.
Published: September 2016

The loss of E-cadherin expression in association with the epithelial–mesenchymal transition (EMT) occurs frequently during tumor metastasis. However, metastases often retain E-cadherin expression, an EMT is not required for metastasis, and metastases can arise from clusters of tumor cells. We demonstrate that the regulation of the adhesive activity of E-cadherin present at the cell surface by an inside-out signaling mechanism is important in cancer. First, we find that the metastasis of an E-cadherin–expressing mammary cell line from the mammary gland to the lung depends on reduced E-cadherin adhesive function. An activating monoclonal antibody to E-cadherin that induces a high adhesive state significantly reduced the number of cells metastasized to the lung without affecting the growth in size of the primary tumor in the mammary gland. Second, we find that many cancer-associated germline missense mutations in the E-cadherin gene in patients with hereditary diffuse gastric cancer selectively affect the mechanism of inside-out cell surface regulation without inhibiting basic E-cadherin adhesion function. This suggests that genetic deficits in E-cadherin cell surface regulation contribute to cancer progression. Analysis of these mutations also provides insights into the molecular mechanisms underlying cadherin regulation at the cell surface.
Proteomic profiling of the mitochondrial ribosome identifies Atp25 as a composite mitochondrial precursor protein
Authors: Woellhaf Michael W. , Sommer Frederik , Schroda Michael , Herrmann Johannes M.
Published: September 2016

Whereas the structure and function of cytosolic ribosomes are well characterized, we only have a limited understanding of the mitochondrial translation apparatus. Using SILAC-based proteomic profiling, we identified 13 proteins that cofractionated with the mitochondrial ribosome, most of which play a role in translation or ribosomal biogenesis. One of these proteins is a homologue of the bacterial ribosome-silencing factor (Rsf). This protein is generated from the composite precursor protein Atp25 upon internal cleavage by the matrix processing peptidase MPP, and in this respect, it differs from all other characterized mitochondrial proteins of baker’s yeast. We observed that cytosolic expression of Rsf, but not of noncleaved Atp25 protein, is toxic. Our results suggest that eukaryotic cells face the challenge of avoiding negative interference from the biogenesis of their two distinct translation machineries.
DeepChrome: deep-learning for predicting gene expression from histone modifications
Authors: Singh Ritambhara , Lanchantin Jack , Robins Gabriel , Qi Yanjun
Published: September 2016

Motivation

Histone modifications are among the most important factors that control gene regulation. Computational methods that predict gene expression from histone modification signals are highly desirable for understanding their combinatorial effects in gene regulation. This knowledge can help in developing ‘epigenetic drugs’ for diseases like cancer. Previous studies for quantifying the relationship between histone modifications and gene expression levels either failed to capture combinatorial effects or relied on multiple methods that separate predictions and combinatorial analysis. This paper develops a unified discriminative framework using a deep convolutional neural network to classify gene expression using histone modification data as input. Our system, called DeepChrome, allows automatic extraction of complex interactions among important features. To simultaneously visualize the combinatorial interactions among histone modifications, we propose a novel optimization-based technique that generates feature pattern maps from the learnt deep model. This provides an intuitive description of underlying epigenetic mechanisms that regulate genes.

Results

We show that DeepChrome outperforms state-of-the-art models like Support Vector Machines and Random Forests for gene expression classification task on 56 different cell-types from REMC database. The output of our visualization technique not only validates the previous observations but also allows novel insights about combinatorial interactions among histone modification marks, some of which have recently been observed by experimental studies.

Availability and Implementation

Codes and results are available at www.deepchrome.org

Contact

yanjun@virginia.edu

Supplementary information

Supplementary data are available at Bioinformatics online.
XGSA: A statistical method for cross-species gene set analysis
Authors: Djordjevic Djordje , Kusumi Kenro , Ho Joshua W K
Published: September 2016

Motivation

Gene set analysis is a powerful tool for determining whether an experimentally derived set of genes is statistically significantly enriched for genes in other pre-defined gene sets, such as known pathways, gene ontology terms, or other experimentally derived gene sets. Current gene set analysis methods do not facilitate comparing gene sets across different organisms as they do not explicitly deal with homology mapping between species. There lacks a systematic investigation about the effect of complex gene homology on cross-species gene set analysis.

Results

In this study, we show that not accounting for the complex homology structure when comparing gene sets in two species can lead to false positive discoveries, especially when comparing gene sets that have complex gene homology relationships. To overcome this bias, we propose a straightforward statistical approach, called XGSA, that explicitly takes the cross-species homology mapping into consideration when doing gene set analysis. Simulation experiments confirm that XGSA can avoid false positive discoveries, while maintaining good statistical power compared to other ad hoc approaches for cross-species gene set analysis. We further demonstrate the effectiveness of XGSA with two real-life case studies that aim to discover conserved or species-specific molecular pathways involved in social challenge and vertebrate appendage regeneration.

Availability and Implementation

The R source code for XGSA is available under a GNU General Public License at http://github.com/VCCRI/XGSA

Contact

jho@victorchang.edu.au
Complementary feature selection from alternative splicing events and gene expression for phenotype prediction
Authors: Labuzzetta Charles J , Antonio Margaret L , Watson Patricia M , Wilson Robert C , Laboissonniere Lauren A , Trimarchi Jeffrey M , Genc Baris , Ozdinler P Hande , Watson Dennis K , Anderson Paul E
Published: September 2016

Motivation

A central task of bioinformatics is to develop sensitive and specific means of providing medical prognoses from biomarker patterns. Common methods to predict phenotypes in RNA-Seq datasets utilize machine learning algorithms trained via gene expression. Isoforms, however, generated from alternative splicing, may provide a novel and complementary set of transcripts for phenotype prediction. In contrast to gene expression, the number of isoforms increases significantly due to numerous alternative splicing patterns, resulting in a prioritization problem for many machine learning algorithms. This study identifies the empirically optimal methods of transcript quantification, feature engineering and filtering steps using phenotype prediction accuracy as a metric. At the same time, the complementary nature of gene and isoform data is analyzed and the feasibility of identifying isoforms as biomarker candidates is examined.

Results

Isoform features are complementary to gene features, providing non-redundant information and enhanced predictive power when prioritized and filtered. A univariate filtering algorithm, which selects up to the N highest ranking features for phenotype prediction is described and evaluated in this study. An empirical comparison of pipelines for isoform quantification is reported by performing cross-validation prediction tests with datasets from human non-small cell lung cancer (NSCLC) patients, human patients with chronic obstructive pulmonary disease (COPD) and amyotrophic lateral sclerosis (ALS) transgenic mice, each including samples of diseased and non-diseased phenotypes.

Availability and Implementation

https://github.com/clabuzze/Phenotype-Prediction-Pipeline.git

Contact

clabuzze@iastate.edu, antoniom@bc.edu, watsondk@musc.edu, andersonpe2@cofc.edu
Mutual enrichment in aggregated ranked lists with applications to gene expression regulation
Authors: Cohn-Alperovich Dalia , Rabner Alona , Kifer Ilona , Mandel-Gutfreund Yael , Yakhini Zohar
Published: September 2016

Motivation

It is often the case in biological measurement data that results are given as a ranked list of quantities—for example, differential expression (DE) of genes as inferred from microarrays or RNA-seq. Recent years brought considerable progress in statistical tools for enrichment analysis in ranked lists. Several tools are now available that allow users to break the fixed set paradigm in assessing statistical enrichment of sets of genes. Continuing with the example, these tools identify factors that may be associated with measured differential expression. A drawback of existing tools is their focus on identifying single factors associated with the observed or measured ranks, failing to address relationships between these factors. For example, a scenario in which genes targeted by multiple miRNAs play a central role in the DE signal but the effect of each single miRNA is too subtle to be detected, as shown in our results.

Results

We propose statistical and algorithmic approaches for selecting a sub-collection of factors that can be aggregated into one ranked list that is heuristically most associated with an input ranked list (pivot). We examine performance on simulated data and apply our approach to cancer datasets. We find small sub-collections of miRNA that are statistically associated with gene DE in several types of cancer, suggesting miRNA cooperativity in driving disease related processes. Many of our findings are consistent with known roles of miRNAs in cancer, while others suggest previously unknown roles for certain miRNAs.

Availability and Implementation

Code and instructions for our algorithmic framework, MULSEA, are in: https://github.com/YakhiniGroup/MULSEA.

Contact

dalia.cohn@gmail.com

Supplementary information

Supplementary data are available at Bioinformatics online.
The Network Library: a framework to rapidly integrate network biology resources
Authors: Summer Georg , Kelder Thomas , Radonjic Marijana , van Bilsen Marc , Wopereis Suzan , Heymans Stephane
Published: September 2016

Motivation

Much of the biological knowledge accumulated over the last decades is stored in different databases governed by various organizations and institutes. Integrating and connecting these vast knowledge repositories is an extremely useful method to support life sciences research and help formulate novel hypotheses.

Results

We developed the Network Library (NL), a framework and toolset to rapidly integrate different knowledge sources to build a network biology resource that matches a specific research question. As a use-case we explore the interactions of genes related to heart failure with miRNAs and diseases through the integration of 6 databases.

Availability and Implementation

The NL is open-source, developed in Java and available on Github (https://github.com/gsummer).

Contact

georg.summer@gmail.com
GTRAC: fast retrieval from compressed collections of genomic variants
Authors: Tatwawadi Kedar , Hernaez Mikel , Ochoa Idoia , Weissman Tsachy
Published: September 2016

Motivation

The dramatic decrease in the cost of sequencing has resulted in the generation of huge amounts of genomic data, as evidenced by projects such as the UK10K and the Million Veteran Project, with the number of sequenced genomes ranging in the order of 10 K to 1 M. Due to the large redundancies among genomic sequences of individuals from the same species, most of the medical research deals with the variants in the sequences as compared with a reference sequence, rather than with the complete genomic sequences. Consequently, millions of genomes represented as variants are stored in databases. These databases are constantly updated and queried to extract information such as the common variants among individuals or groups of individuals. Previous algorithms for compression of this type of databases lack efficient random access capabilities, rendering querying the database for particular variants and/or individuals extremely inefficient, to the point where compression is often relinquished altogether.

Results

We present a new algorithm for this task, called GTRAC, that achieves significant compression ratios while allowing fast random access over the compressed database. For example, GTRAC is able to compress a Homo sapiens dataset containing 1092 samples in 1.1 GB (compression ratio of 160), while allowing for decompression of specific samples in less than a second and decompression of specific variants in 17 ms. GTRAC uses and adapts techniques from information theory, such as a specialized Lempel-Ziv compressor, and tailored succinct data structures.

Availability and Implementation

The GTRAC algorithm is available for download at: https://github.com/kedartatwawadi/GTRAC

Contact

kedart@stanford.edu

Supplementary information

Supplementary data are available at Bioinformatics online.
Combining dependentP-values with an empirical adaptation of Brown’s method
Authors: Poole William , Gibbs David L , Shmulevich Ilya , Bernard Brady , Knijnenburg Theo A
Published: September 2016

Motivation

Combining P-values from multiple statistical tests is a common exercise in bioinformatics. However, this procedure is non-trivial for dependent P-values. Here, we discuss an empirical adaptation of Brown’s method (an extension of Fisher’s method) for combining dependent P-values which is appropriate for the large and correlated datasets found in high-throughput biology.

Results

We show that the Empirical Brown’s method (EBM) outperforms Fisher’s method as well as alternative approaches for combining dependent P-values using both noisy simulated data and gene expression data from The Cancer Genome Atlas.

Availability and Implementation

The Empirical Brown’s method is available in Python, R, and MATLAB and can be obtained from https://github.com/IlyaLab/CombiningDependentPvalues UsingEBM. The R code is also available as a Bioconductor package from https://www.bioconductor.org/packages/devel/bioc/html/EmpiricalBrownsMethod.html.

Contact

Theo.Knijnenburg@systemsbiology.org

Supplementary information

Supplementary data are available at Bioinformatics online.
AUCpreD: proteome-level protein disorder prediction by AUC-maximized deep convolutional neural fields
Authors: Wang Sheng , Ma Jianzhu , Xu Jinbo
Published: September 2016

Motivation

Protein intrinsically disordered regions (IDRs) play an important role in many biological processes. Two key properties of IDRs are (i) the occurrence is proteome-wide and (ii) the ratio of disordered residues is about 6%, which makes it challenging to accurately predict IDRs. Most IDR prediction methods use sequence profile to improve accuracy, which prevents its application to proteome-wide prediction since it is time-consuming to generate sequence profiles. On the other hand, the methods without using sequence profile fare much worse than using sequence profile.

Method

This article formulates IDR prediction as a sequence labeling problem and employs a new machine learning method called Deep Convolutional Neural Fields (DeepCNF) to solve it. DeepCNF is an integration of deep convolutional neural networks (DCNN) and conditional random fields (CRF); it can model not only complex sequence–structure relationship in a hierarchical manner, but also correlation among adjacent residues. To deal with highly imbalanced order/disorder ratio, instead of training DeepCNF by widely used maximum-likelihood, we develop a novel approach to train it by maximizing area under the ROC curve (AUC), which is an unbiased measure for class-imbalanced data.

Results

Our experimental results show that our IDR prediction method AUCpreD outperforms existing popular disorder predictors. More importantly, AUCpreD works very well even without sequence profile, comparing favorably to or even outperforming many methods using sequence profile. Therefore, our method works for proteome-wide disorder prediction while yielding similar or better accuracy than the others.

Availability and Implementation

http://raptorx2.uchicago.edu/StructurePropertyPred/predict/

Contact

wangsheng@uchicago.edu, jinboxu@gmail.com

Supplementary information

Supplementary data are available at Bioinformatics online.
PeakXus: comprehensive transcription factor binding site discovery from ChIP-Nexus and ChIP-Exo experiments
Authors: Hartonen Tuomo , Sahu Biswajyoti , Dave Kashyap , Kivioja Teemu , Taipale Jussi
Published: September 2016

Motivation

Transcription factor (TF) binding can be studied accurately in vivo with ChIP-exo and ChIP-Nexus experiments. Only fraction of TF binding mechanisms are yet fully understood and accurate knowledge of binding locations and patterns of TFs is key to understanding binding that is not explained by simple positional weight matrix models. ChIP-exo/Nexus experiments can also offer insight on the effect of single nucleotide polymorphism (SNP) at TF binding sites on expression of the target genes. This is an important mechanism of action for disease-causing SNPs at non-coding genomic regions.

Results

We describe a peak caller PeakXus that is specifically designed to leverage the increased resolution of ChIP-exo/Nexus and developed with the aim of making as few assumptions of the data as possible to allow discoveries of novel binding patterns. We apply PeakXus to ChIP-Nexus and ChIP-exo experiments performed both in Homo sapiens and in Drosophila melanogaster cell lines. We show that PeakXus consistently finds more peaks overlapping with a TF-specific recognition sequence than published methods. As an application example we demonstrate how PeakXus can be coupled with unique molecular identifiers (UMIs) to measure the effect of a SNP overlapping with a TF binding site on the in vivo binding of the TF.

Availability and Implementation

Source code of PeakXus is available at https://github.com/hartonen/PeakXus

Contact

tuomo.hartonen@helsinki.fi or jussi.taipale@ki.se
Characterizing leader sequences of CRISPR loci
Authors: Alkhnbashi Omer S , Shah Shiraz A , Garrett Roger A , Saunders Sita J , Costa Fabrizio , Backofen Rolf
Published: September 2016

Motivation

The CRISPR-Cas system is an adaptive immune system in many archaea and bacteria, which provides resistance against invading genetic elements. The first phase of CRISPR-Cas immunity is called adaptation, in which small DNA fragments are excised from genetic elements and are inserted into a CRISPR array generally adjacent to its so called leader sequence at one end of the array. It has been shown that transcription initiation and adaptation signals of the CRISPR array are located within the leader. However, apart from promoters, there is very little knowledge of sequence or structural motifs or their possible functions. Leader properties have mainly been characterized through transcriptional initiation data from single organisms but large-scale characterization of leaders has remained challenging due to their low level of sequence conservation.

Results

We developed a method to successfully detect leader sequences by focusing on the consensus repeat of the adjacent CRISPR array and weak upstream conservation signals. We applied our tool to the analysis of a comprehensive genomic database and identified several characteristic properties of leader sequences specific to archaea and bacteria, ranging from distinctive sizes to preferential indel localization. CRISPRleader provides a full annotation of the CRISPR array, its strand orientation as well as conserved core leader boundaries that can be uploaded to any genome browser. In addition, it outputs reader-friendly HTML pages for conserved leader clusters from our database.

Availability and Implementation

CRISPRleader and multiple sequence alignments for all 195 leader clusters are available at http://www.bioinf.uni-freiburg.de/Software/CRISPRleader/.

Contact

costa@informatik.uni-freiburg.de or backofen@informatik.uni-freiburg.de

Supplementary information

Supplementary data are available at Bioinformatics online.
Improve homology search sensitivity of PacBio data by correcting frameshifts
Authors: Du Nan , Sun Yanni
Published: September 2016

Motivation

Single-molecule, real-time sequencing (SMRT) developed by Pacific BioSciences produces longer reads than secondary generation sequencing technologies such as Illumina. The long read length enables PacBio sequencing to close gaps in genome assembly, reveal structural variations, and identify gene isoforms with higher accuracy in transcriptomic sequencing. However, PacBio data has high sequencing error rate and most of the errors are insertion or deletion errors. During alignment-based homology search, insertion or deletion errors in genes will cause frameshifts and may only lead to marginal alignment scores and short alignments. As a result, it is hard to distinguish true alignments from random alignments and the ambiguity will incur errors in structural and functional annotation. Existing frameshift correction tools are designed for data with much lower error rate and are not optimized for PacBio data. As an increasing number of groups are using SMRT, there is an urgent need for dedicated homology search tools for PacBio data.

Results

In this work, we introduce Frame-Pro, a profile homology search tool for PacBio reads. Our tool corrects sequencing errors and also outputs the profile alignments of the corrected sequences against characterized protein families. We applied our tool to both simulated and real PacBio data. The results showed that our method enables more sensitive homology search, especially for PacBio data sets of low sequencing coverage. In addition, we can correct more errors when comparing with a popular error correction tool that does not rely on hybrid sequencing.

Availability and Implementation

The source code is freely available at https://sourceforge.net/projects/frame-pro/.

Contact

yannisun@msu.edu
Fast genotyping of known SNPs through approximate k-mer matching
Authors: Shajii Ariya , Yorukoglu Deniz , William Yu Yun , Berger Bonnie
Published: September 2016

Motivation

As the volume of next-generation sequencing (NGS) data increases, faster algorithms become necessary. Although speeding up individual components of a sequence analysis pipeline (e.g. read mapping) can reduce the computational cost of analysis, such approaches do not take full advantage of the particulars of a given problem. One problem of great interest, genotyping a known set of variants (e.g. dbSNP or Affymetrix SNPs), is important for characterization of known genetic traits and causative disease variants within an individual, as well as the initial stage of many ancestral and population genomic pipelines (e.g. GWAS).

Results

We introduce lightweight assignment of variant alleles (LAVA), an NGS-based genotyping algorithm for a given set of SNP loci, which takes advantage of the fact that approximate matching of mid-size k-mers (with k = 32) can typically uniquely identify loci in the human genome without full read alignment. LAVA accurately calls the vast majority of SNPs in dbSNP and Affymetrix’s Genome-Wide Human SNP Array 6.0 up to about an order of magnitude faster than standard NGS genotyping pipelines. For Affymetrix SNPs, LAVA has significantly higher SNP calling accuracy than existing pipelines while using as low as ∼5 GB of RAM. As such, LAVA represents a scalable computational method for population-level genotyping studies as well as a flexible NGS-based replacement for SNP arrays.

Availability and Implementation

LAVA software is available at http://lava.csail.mit.edu.

Contact

bab@mit.edu

Supplementary information

Supplementary data are available at Bioinformatics online.
Bayesian parameter estimation for the Wnt pathway: an infinite mixture models approach
Authors: Koutroumpas Konstantinos , Ballarini Paolo , Votsi Irene , Cournède Paul-Henry
Published: September 2016

Motivation

Likelihood-free methods, like Approximate Bayesian Computation (ABC), have been extensively used in model-based statistical inference with intractable likelihood functions. When combined with Sequential Monte Carlo (SMC) algorithms they constitute a powerful approach for parameter estimation and model selection of mathematical models of complex biological systems. A crucial step in the ABC–SMC algorithms, significantly affecting their performance, is the propagation of a set of parameter vectors through a sequence of intermediate distributions using Markov kernels.

Results

In this article, we employ Dirichlet process mixtures (DPMs) to design optimal transition kernels and we present an ABC–SMC algorithm with DPM kernels. We illustrate the use of the proposed methodology using real data for the canonical Wnt signaling pathway. A multi-compartment model of the pathway is developed and it is compared to an existing model. The results indicate that DPMs are more efficient in the exploration of the parameter space and can significantly improve ABC–SMC performance. In comparison to alternative sampling schemes that are commonly used, the proposed approach can bring potential benefits in the estimation of complex multimodal distributions. The method is used to estimate the parameters and the initial state of two models of the Wnt pathway and it is shown that the multi-compartment model fits better the experimental data.

Availability and Implementation

Python scripts for the Dirichlet Process Gaussian Mixture model and the Gibbs sampler are available at https://sites.google.com/site/kkoutroumpas/software.

Contact

konstantinos.koutroumpas@ecp.fr
Overwintering Stages of Pseudosclerotia Development for Monilinia vaccinii-corymbosi, Causal Agent of Mummy Berry Disease on Highbush Blueberry in North America
Authors: Florence Jade , Pscheidt Jay W.
Published: September 2016

Mummy berry, caused by Monilinia vaccinii-corymbosi, is an economically important disease of blueberries throughout North America. Pseudosclerotia develop apothecia and produce primary inoculum in coordination with floral bud break. Terminology for M. vaccinii-corymbosi pseudosclerotial overwintering stages is inconsistent throughout the literature, and the progression from development to sporulation has never been cohesively and sequentially outlined. A developmental classification scheme was derived from existing terminology and observations of naturally-conditioned pseudosclerotia over a two-year period in Corvallis, OR. The proposed terminology for pseudosclerotial overwintering stages include maturation, dormancy, germination, emergence, differentiation, and carpogenic germination. The standardization of these terms will allow researchers to better communicate regarding this pathogen.

Accepted for publication 19 July 2016. Published 15 August 2016.
A Standardized Inoculation Protocol to Test Wheat Cultivars for Reaction to Head Blast Caused by Magnaporthe oryzae (Triticum pathotype)
Authors: Cruz C. D. , Bockus W. W. , Stack J. P. , Valent B. , Maciel J. N. , Peterson G. L.
Published: September 2016

Wheat blast, caused by the Triticum pathotype of Magnaporthe oryzae, poses a significant threat to wheat production worldwide. Because this pathotype does not occur in the United States, it is important to prepare for its possible introduction. As part of this preparation, over 500 U.S. wheat cultivars were tested for susceptibility or resistance to head blast. Inoculations were conducted under biosafety level 3 conditions. However, the protocols to phenotype wheat cultivars vary among researchers, and head blast inoculation protocols need to be standardized so that results can be easily interpreted and shared internationally. The protocol presented, based on several years' experience, is recommended for common use to facilitate direct comparison of disease phenotyping results among researchers.

Accepted for publication 12 August 2016.
Polyoxin D and Other Biopesticides Reduce Gummy Stem Blight But Not Anthracnose on Melon Seedlings
Authors: Keinath Anthony P.
Published: September 2016

Biopesticides may be useful to prevent fungal foliar diseases on cucurbit seedlings in greenhouses because of the short re-entry intervals, normally 4 h. Bacillus subtilis QST 713 (Serenade ASO), root extract of Reynoutria sachalinensis (Regalia), hydrogen dioxide (Oxidate), paraffinic oil (JMS Stylet Oil), polyoxin D (Oso), and 92% edible fish oil + 5% sesame oil (Organocide) were evaluated against gummy stem blight on muskmelon seedlings and anthracnose on watermelon seedlings. Polyoxin D applied alone, B. subtilis QST 713 followed by polyoxin D, and R. sachalinensis extract followed by B. subtilis QST 713 reduced the severity of gummy stem blight and were as effective as mancozeb. None of the biopesticides applied alone or sequentially were effective against anthracnose. Polyoxin D could be used to prevent outbreaks of gummy stem blight on watermelon and muskmelon seedlings grown for use as transplants.

Accepted for publication 1 July 2016. Published 4 August 2016.
Comparison of Two Soil Sampling Methods for Estimating Population Densities of Heterodera glycines Cysts
Authors: Smrtnik Ethan , Niblack Terry , Paul Pierce , Dorrance Anne , Bruns Dain
Published: September 2016

Soybean cyst nematode (SCN) is a significant economic pest of soybean in Ohio and the Midwest, in which yield losses are directly linked to the population density and distribution of cysts within a field. Advances in automation technology have been used to expedite soil fertility sampling for large-scale and high-density field maps. In this study, we explored the use of this technology as an option for sampling for SCN. There was a significant positive correlation for the number of SCN cysts between soil samples collected with an Automated Precision Soil Sampler and those collected using the traditional soil sampling method from three separate fields (P < 0.05, r values of 0.79 to 0.93). These results suggest that expedited soil sampling in fields with high population densities could be an added benefit for soybean farmers to encourage more sampling for SCN to monitor population levels as part of their overall management program.

Accepted for publication 18 July 2016. Published 12 August 2016.
Influence of a Therapeutic Soft Contact Lens on Epithelial Healing, Visual Recovery, Haze, and Pain After Photorefractive Keratectomy
Authors: Taneri Suphi , Oehler Saskia , MacRae Scott , Dick H. Burkhard
Published: September 2016

Objectives:

To examine the influence of a therapeutic soft contact lens (TSCL) after alcohol-assisted photorefractive keratectomy (PRK) on visual recovery, epithelial closure, pain perception, and haze formation.

Methods:

Prospective, randomized, single-center, contralateral eye, patient-masked study. Same surgeon treated 15 patients with bilateral PRK using a Vidaurri Fluid Retention Ring (Katena) with 8.7 mm inner diameter to apply ethanol 18% for 30 sec. Each patient received a TSCL (Balafilcon A, PureVision, Bausch & Lomb) in a randomized fashion in one eye only.

Results:

Without knowing which eye had a contact lens, four patients preferred the eye with TSCL so much that these patients wanted a TSCL inserted in the second eye as well. Uncorrected distance visual acuity improved postoperatively from day 1 to 3 months from 0.61 to 1.18 with TSCL and from 0.21 to 1.04 without TSCL. Uncorrected distance visual acuity was statistically significantly better on days 1 and 2 with TSCL. Epithelial defect was on average smaller with TSCL. Epithelium was closed at day 4 in all eyes except one without TSCL. Pain perception was significantly lower with TSCL on days 1 and 2. Haze levels after 3 months were significantly lower with TSCL (with 0.09/without 0.45, respectively). One eye without TSCL had haze grade 2 (Fantes).

Conclusions:

A TSCL had statistically significantly and clinically meaningful beneficial effects in the first days in visual recovery and pain perception and after 3 months in haze formation. Epithelial healing was slightly quicker with the use of TSCLs (not statistically, but clinically significantly).