bluuebunny/crossref_metadata_2025_split huggingface dataset:
MetaBMF: a scalable binning algorithm for large-scale reference-free metagenomic studies
Authors: Ma Terry , Xiao Di , Xing Xin 
Published: July 2019

AbstractMotivationMetagenomics studies microbial genomes in an ecosystem such as the gastrointestinal tract of a human. Identification of novel microbial species and quantification of their distributional variations among different samples that are sequenced using next-generation-sequencing technology hold the key to the success of most metagenomic studies. To achieve these goals, we propose a simple yet powerful metagenomic binning method, MetaBMF. The method does not require prior knowledge of reference genomes and produces highly accurate results, even at a strain level. Thus, it can be broadly used to identify disease-related microbial organisms that are not well-studied.ResultsMathematically, we count the number of mapped reads on each assembled genomic fragment cross different samples as our input matrix and propose a scalable stratified angle regression algorithm to factorize this count matrix into a product of a binary matrix and a nonnegative matrix. The binary matrix can be used to separate microbial species and the nonnegative matrix quantifies the species distributions in different samples. In simulation and empirical studies, we demonstrate that MetaBMF has a high binning accuracy. It can not only bin DNA fragments accurately at a species level but also at a strain level. As shown in our example, we can accurately identify the Shiga-toxigenic Escherichia coli O104: H4 strain which led to the 2011 German E.coli outbreak. Our efforts in these areas should lead to (i) fundamental advances in metagenomic binning, (ii) development and refinement of technology for the rapid identification and quantification of microbial distributions and (iii) finding of potential probiotics or reliable pathogenic bacterial strains.Availability and implementationThe software is available at https://github.com/didi10384/MetaBMF.
DR-SIP: protocols for higher order structure modeling with distance restraints- and cyclic symmetry-imposed packing
Authors: Chan Justin , Zou Jinhao , Ortiz Christopher Llynard , Chang Chien Chi-Hong , Pan Rong-Long , Yang Lee-Wei 
Published: July 2019

Abstract

Motivation
Quaternary structure determination for transmembrane/soluble proteins requires a reliable computational protocol that leverages observed distance restraints and/or cyclic symmetry (Cn symmetry) found in most homo-oligomeric transmembrane proteins.

Results
We survey 118 X-ray crystallographically solved structures of homo-oligomeric transmembrane proteins (HoTPs) and find that ∼97% are Cn symmetric. Given the prevalence of Cn symmetric HoTPs and the benefits of incorporating geometry restraints in aiding quaternary structure determination, we introduce two new filters, the distance-restraints (DR) and the Symmetry-Imposed Packing (SIP) filters. SIP relies on a new method that can rebuild the closest ideal Cn symmetric complex from docking poses containing a homo-dimer without prior knowledge of the number (n) of monomers. Using only the geometrical filter, SIP, near-native poses of 7 HoTPs in their monomeric states can be correctly identified in the top-10 for 71% of all cases, or 29% among 31 HoTP structures obtained through homology modeling, while ZDOCK alone returns 14 and 3%, respectively. When the n is given, the optional n-mer filter is applied with SIP and returns the near-native poses for 76% of the test set within the top-10, outperforming M-ZDOCK’s 55% and Sam’s 47%. While applying only SIP to three HoTPs that comes with distance restraints, we found the near-native poses were ranked 1st, 1st and 10th among 54 000 possible decoys. The results are further improved to 1st, 1st and 3rd when both DR and SIP filters are used. By applying only DR, a soluble system with distance restraints is recovered at the 1st-ranked pose.

Availability and implementation
https://github.com/capslockwizard/drsip.

Supplementary information
Supplementary data are available at Bioinformatics online.
Efficient parameterization of large-scale dynamic models based on relative measurements
Authors: Schmiester Leonard , Schälte Yannik , Fröhlich Fabian , Hasenauer Jan , Weindl Daniel 
Published: July 2019

AbstractMotivationMechanistic models of biochemical reaction networks facilitate the quantitative understanding of biological processes and the integration of heterogeneous datasets. However, some biological processes require the consideration of comprehensive reaction networks and therefore large-scale models. Parameter estimation for such models poses great challenges, in particular when the data are on a relative scale.ResultsHere, we propose a novel hierarchical approach combining (i) the efficient analytic evaluation of optimal scaling, offset and error model parameters with (ii) the scalable evaluation of objective function gradients using adjoint sensitivity analysis. We evaluate the properties of the methods by parameterizing a pan-cancer ordinary differential equation model (&gt;1000 state variables, &gt;4000 parameters) using relative protein, phosphoprotein and viability measurements. The hierarchical formulation improves optimizer performance considerably. Furthermore, we show that this approach allows estimating error model parameters with negligible computational overhead when no experimental estimates are available, providing an unbiased way to weight heterogeneous data. Overall, our hierarchical formulation is applicable to a wide range of models, and allows for the efficient parameterization of large-scale models based on heterogeneous relative measurements.Availability and implementationSupplementary code and data are available online at http://doi.org/10.5281/zenodo.3254429 and http://doi.org/10.5281/zenodo.3254441.Supplementary informationSupplementary data are available at Bioinformatics online.
pourRNA—a time- and memory-efficient approach for the guided exploration of RNA energy landscapes
Authors: Entzian Gregor , Raden Martin 
Published: July 2019

Abstract

Motivation
The folding dynamics of ribonucleic acids (RNAs) are typically studied via coarse-grained models of the underlying energy landscape to face the exponential growths of the RNA secondary structure space. Still, studies of exact folding kinetics based on gradient basin abstractions are currently limited to short sequence lengths due to vast memory requirements. In order to compute exact transition rates between gradient basins, state-of-the-art approaches apply global flooding schemes that require to memorize the whole structure space at once. pourRNA tackles this problem via local flooding techniques where memorization is limited to the structure ensembles of individual gradient basins.

Results
Compared to the only available tool for exact gradient basin-based macro-state transition rates (namely barriers), pourRNA computes the same exact transition rates up to 10 times faster and requires two orders of magnitude less memory for sequences that are still computationally accessible for exhaustive enumeration. Parallelized computation as well as additional heuristics further speed up computations while still producing high-quality transition model approximations. The introduced heuristics enable a guided trade-off between model quality and required computational resources. We introduce and evaluate a macroscopic direct path heuristics to efficiently compute refolding energy barrier estimations for the co-transcriptionally trapped RNA sv11 of length 115 nt. Finally, we also show how pourRNA can be used to identify folding funnels and their respective energetically lowest minima.

Availability and implementation
pourRNA is freely available at https://github.com/ViennaRNA/pourRNA.

Supplementary information
Supplementary data are available at Bioinformatics online.
DISPOT: a simple knowledge-based protein domain interaction statistical potential
Authors: Narykov Oleksandr , Bogatov Dmytro , Korkin Dmitry 
Published: July 2019

Abstract

Motivation
The complexity of protein–protein interactions (PPIs) is further compounded by the fact that an average protein consists of two or more domains, structurally and evolutionary independent subunits. Experimental studies have demonstrated that an interaction between a pair of proteins is not carried out by all domains constituting each protein, but rather by a select subset. However, determining which domains from each protein mediate the corresponding PPI is a challenging task.

Results
Here, we present domain interaction statistical potential (DISPOT), a simple knowledge-based statistical potential that estimates the propensity of an interaction between a pair of protein domains, given their structural classification of protein (SCOP) family annotations. The statistical potential is derived based on the analysis of &gt;352 000 structurally resolved PPIs obtained from DOMMINO, a comprehensive database of structurally resolved macromolecular interactions.

Availability and implementation
DISPOT is implemented in Python 2.7 and packaged as an open-source tool. DISPOT is implemented in two modes, basic and auto-extraction. The source code for both modes is available on GitHub: https://github.com/korkinlab/dispot and standalone docker images on DockerHub: https://hub.docker.com/r/korkinlab/dispot. The web server is freely available at http://dispot.korkinlab.org/.

Supplementary information
Supplementary data are available at Bioinformatics online.
P-value evaluation, variability index and biomarker categorization for adaptively weighted Fisher’s meta-analysis method in omics applications
Authors: Huo Zhiguang , Tang Shaowu , Park Yongseok , Tseng George 
Published: July 2019

AbstractMotivationMeta-analysis methods have been widely used to combine results from multiple clinical or genomic studies to increase statistical powers and ensure robust and accurate conclusions. The adaptively weighted Fisher’s method (AW-Fisher), initially developed for omics applications but applicable for general meta-analysis, is an effective approach to combine P-values from K independent studies and to provide better biological interpretability by characterizing which studies contribute to the meta-analysis. Currently, AW-Fisher suffers from the lack of fast P-value computation and variability estimate of AW weights. When the number of studies K is large, the 3K − 1 possible differential expression pattern categories generated by AW-Fisher can become intractable. In this paper, we develop an importance sampling scheme with spline interpolation to increase the accuracy and speed of the P-value calculation. We also apply bootstrapping to construct a variability index for the AW-Fisher weight estimator and a co-membership matrix to categorize (cluster) differentially expressed genes based on their meta-patterns for intuitive biological investigations.ResultsThe superior performance of the proposed methods is shown in simulations as well as two real omics meta-analysis applications to demonstrate its insightful biological findings.Availability and implementationAn R package AWFisher (calling C++) is available at Bioconductor and GitHub (https://github.com/Caleb-Huo/AWFisher), and all datasets and programing codes for this paper are available in the Supplementary Material.Supplementary informationSupplementary data are available at Bioinformatics online.
Identifying small-effect genetic associations overlooked by the conventional fixed-effect model in a large-scale meta-analysis of coronary artery disease
Authors: Magosi Lerato E , Goel Anuj , Hopewell Jemma C , Farrall Martin 
Published: July 2019

Abstract

Motivation
Common small-effect genetic variants that contribute to human complex traits and disease are typically identified using traditional fixed-effect (FE) meta-analysis methods. However, the power to detect genetic associations under FE models deteriorates with increasing heterogeneity, so that some small-effect heterogeneous loci might go undetected. A modified random-effects meta-analysis approach (RE2) was previously developed that is more powerful than traditional fixed and random-effects methods at detecting small-effect heterogeneous genetic associations, the method was updated (RE2C) to identify small-effect heterogeneous variants overlooked by traditional fixed-effect meta-analysis. Here, we re-appraise a large-scale meta-analysis of coronary disease with RE2C to search for small-effect genetic signals potentially masked by heterogeneity in a FE meta-analysis.

Results
Our application of RE2C suggests a high sensitivity but low specificity of this approach for discovering small-effect heterogeneous genetic associations. We recommend that reports of small-effect heterogeneous loci discovered with RE2C are accompanied by forest plots and standardized predicted random-effects statistics to reveal the distribution of genetic effect estimates across component studies of meta-analyses, highlighting overly influential outlier studies with the potential to inflate genetic signals.

Availability and implementation
Scripts to calculate standardized predicted random-effects statistics and generate forest plots are available in the getspres R package entitled from https://magosil86.github.io/getspres/.

Supplementary information
Supplementary data are available at Bioinformatics online.
Homelessness in a Post-Soviet City: Weak Social Support and Institutional Alienation
Authors: Negură Petru 
Published: July 2019

AbstractResearch has shown that most homeless people suffer from weak support from family, relatives and friends. Based on a descriptive statistical analysis with biographical records of 810 subjects, and a thematic analysis of interviews with homeless people (N = 65), people at risk of homelessness (N = 5) and professionals (N = 20), the article explores the social support system of homeless people from Chisinau (Moldova). Only 18.6 per cent of all users of the Shelter for homeless in Chisinau were in a couple relationship (and only 5.6 per cent registered officially). For former detainees (23 per cent of the Shelter users) and care leavers (11 per cent), it is even more difficult to create a couple and to strengthen their social support network, as the institutions they come from did not foster their social support. As homelessness becomes chronic, people build social support networks with other homeless people. This social support helps homeless people to cope with stressful living conditions. The article suggests, in the case of Moldova, that social support relations with family, friends, acquaintances and other homeless people are affected negatively in the absence of policies and institutional measures targeted to encourage and strengthen such relationships.
The phylogeography of Vellozia auriculata (Velloziaceae) supports low zygotic gene flow and local population persistence in the campo rupestre, a Neotropical OCBIL
Authors: Fiorini Cecilia F , Miranda Marina Dutra , Silva-Pereira Viviane , Barbosa Ariane Raquel , Oliveira Ubirajara De , Kamino Luciana Hiromi Yoshino , Mota Nara Furtado De Oliveira , Viana Pedro Lage , Borba Eduardo Leite 
Published: July 2019

AbstractThe campo rupestre is a Neotropical azonal vegetation. Its disjoint distribution and the fact that it is an old climatic buffered infertile landscape (OCBIL) have been associated with the high diversity and endemism observed in this environment. Here, we tested whether a micro-endemic species from campo rupestre shows: (1) limited zygotic gene flow; (2) lower gametic than zygotic gene flow structure; (3) substrate-driven genetic structure and (4) no evidence of Pleistocene local extinction or recolonization. By sequencing intergenic plastid regions, phenotyping inter simple sequence repeats (ISSR) and modelling present and past species suitability distributions for Vellozia auriculata we conclude that (1) zygotic gene flow is limited; (2) gametic gene flow is recurrent, but limited by elevation and distance; (3) there is no support for genetic structure driven by substrate and (4) Pleistocene climatic changes did not restrict the species to refugia, with local persistence. As long-term gene flow restrictions may lead to differentiation and speciation, our data helps to corroborate that the campo rupestre is both a cradle (due to low zygotic gene flow, prolonged isolation and consequent differentiation) and a lineage museum (due to local survival during climate oscillations). We highlight two distinct evolutionarily significant units (ESU), providing information for better conservation practice.
Functional Integration of Neuronal Precursors in the Adult Murine Piriform Cortex
Authors: Benedetti Bruno , Dannehl Dominik , König Richard , Coviello Simona , Kreutzer Christina , Zaunmair Pia , Jakubecova Dominika , Weiger Thomas M , Aigner Ludwig , Nacher Juan , Engelhardt Maren , Couillard-Després Sébastien 
Published: July 2019

Abstract
The extent of functional maturation and integration of nonproliferative neuronal precursors, becoming neurons in the adult murine piriform cortex, is largely unexplored. We thus questioned whether precursors eventually become equivalent to neighboring principal neurons or whether they represent a novel functional network element. Adult brain neuronal precursors and immature neurons (complex cells) were labeled in transgenic mice (DCX-DsRed and DCX-CreERT2 /flox-EGFP), and their cell fate was characterized with patch clamp experiments and morphometric analysis of axon initial segments. Young (DCX+) complex cells in the piriform cortex of 2- to 4-month-old mice received sparse synaptic input and fired action potentials at low maximal frequency, resembling neonatal principal neurons. Following maturation, the synaptic input detected on older (DCX−) complex cells was larger, but predominantly GABAergic, despite evidence of glutamatergic synaptic contacts. Furthermore, the rheobase current of old complex cells was larger and the maximal firing frequency was lower than those measured in neighboring age-matched principal neurons. The striking differences between principal neurons and complex cells suggest that the latter are a novel type of neuron and new coding element in the adult brain rather than simple addition or replacement for preexisting network components.
Development and Validation of HPLC and HPTLC Methods for Therapeutic Drug Monitoring of Capecitabine in Colorectal Cancer Patients
Authors: Thorat Sonali G , Chikhale Rupesh V , Tajne Madhukar R 
Published: July 2019

Abstract
Capecitabine is a prodrug of 5-fluorouracil, employed as a monotherapy or combination chemotherapy agent for treatment of colorectal cancer. Combination therapy of capecitabine consists of oxaliplatin, and hence, it becomes essential to determine that co-administration does not affect its metabolism. High-performance liquid chromatography and high-performance thin-layer chromatography methods were developed and validated to determine the plasma concentration of capecitabine. In this study, blood samples from 12 patients with colorectal cancer were collected and analyzed by both methods with a reference internal standard. Two groups consisting of six patients each were formed: the first group was treated with capecitabine monotherapy, the second group with capecitabine + oxaliplatin combination therapy. The results of analysis from both the methods indicated that there is no significant drug–drug interaction. The co-administration of oxaliplatin did not affect the metabolism of capecitabine. Both assay methods were compared for their sensitivity, robustness and specificity. It was found that both the assay methods were suitable for therapeutic drug monitoring of capecitabine.
Development and validation of a HPLC-UV method for the simultaneous detection and quantification of paclitaxel and sulforaphane in lipid based self-microemulsifying formulation
Authors: Kamal Mohammad M , Nazzal Sami 
Published: July 2019

AbstractPaclitaxel (PTX) and sulforaphane (SFN) are known anticancer molecules. Their activity was found to be potentiated when tested concurrently. Only recently, however, a novel SFN enabled PTX self-microemulsifying formulation (SMEDDS) was developed for their simultaneous delivery. This necessitated the development of an analytical method for the simultaneous detection and quantitation of PTX and SFN. In this study, a simple and sensitive isocratic high performance liquid chromatography-ultraviolet (HPLC-UV) analytical method was developed and validated per International Conference on Harmonization guidelines to satisfy this objective. Its application was demonstrated when quantifying the amount of PTX and SFN released from the SMEDDS in various dissolution media. The separation of the analytes was performed with the aid of a reversed phase C18 column at ambient temperature using a 60:40 mixture of acetonitrile and KH2PO4 buffer (pH 5.0) as the mobile phase. PTX and SFN peaks were detected at 202 nm with high resolution without interference from excipients. This method showed linearity within 2.5–100 μg/mL range with r2 &gt; 0.999. The limit of detection and lower limit of quantitation were 0.1638 and 0.4964 μg/mL for PTX and 0.4419 and 1.3389 μg/mL for SFN, respectively. A total of 98–101% of the injected samples was recovered with RSD of 0.06–0.68% indicating the suitability of the method for the simultaneous detection and quantitation of the molecules in dissolution media.
Generating the Evidence for Typhoid Vaccine Introduction: Considerations for Global Disease Burden Estimates and Vaccine Testing Through Human Challenge
Authors: Meiring James E , Giubilini Alberto , Savulescu Julian , Pitzer Virginia E , Pollard Andrew J 
Published: July 2019

AbstractTyphoid fever has had a major impact on human populations, with the causative pathogen Salmonella enterica serovar Typhi implicated in many outbreaks through history. The current burden of disease is estimated at 11–18 million infections annually, with the majority of infections located in Africa and South Asia. Data that have been used to estimate burden are limited to a small number of blood-culture surveillance studies, largely from densely populated urban centers. Extrapolating these data to estimate disease burden within and across countries highlights the lack of precision in global figures. A number of approaches have been developed, characterizing different geographical areas by water-based risk factors for typhoid infection or broader measures of health and development to more accurately extrapolate incidence. Recognition of the substantial disease burden is essential for policy-makers considering vaccine introduction. Typhoid vaccines have been in development for &gt;100 years. The Vi polysaccharide (ViPS) and Ty21a vaccines have had a World Health Organization (WHO) recommendation for programmatic use in countries with high burden for 10 years, with 1 ViPS vaccine also having WHO prequalification. Despite this, uptake and introduction of these vaccines has been minimal. The development of a controlled human infection model (CHIM) enabled the accelerated testing of the newly WHO-prequalified ViPS–tetanus toxoid protein conjugate vaccine, providing efficacy estimates for the vaccine, prior to larger field trials. There is an urgency to the global control of enteric fever due to the escalating problem of antimicrobial resistance. With more accurate burden of disease estimates and a vaccine showing efficacy in CHIM, that control is now a possibility.