bluuebunny/crossref_metadata_2025_split huggingface dataset:
New KEGG pathway-based interpretable features for classifying ageing-related mouse proteins
Authors: Fabris Fabio , Freitas Alex A. 
Published: June 2016

Abstract
Motivation: The incidence of ageing-related diseases has been constantly increasing in the last decades, raising the need for creating effective methods to analyze ageing-related protein data. These methods should have high predictive accuracy and be easily interpretable by ageing experts. To enable this, one needs interpretable classification models (supervised machine learning) and features with rich biological meaning. In this paper we propose two interpretable feature types based on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and compare them with traditional feature types in hierarchical classification (a more challenging classification task regarding predictive performance) and binary classification (a classification task producing easier to interpret classification models). As far as we know, this work is the first to: (i) explore the potential of the KEGG pathway data in the hierarchical classification setting, (i) use the graph structure of KEGG pathways to create a feature type that quantifies the influence of a current protein on another specific protein within a KEGG pathway graph and (iii) propose a method for interpreting the classification models induced using KEGG features.
Results: We performed tests measuring predictive accuracy considering hierarchical and binary class labels extracted from the Mouse Phenotype Ontology. One of the KEGG feature types leads to the highest predictive accuracy among five individual feature types across three hierarchical classification algorithms. Additionally, the combination of the two KEGG feature types proposed in this work results in one of the best predictive accuracies when using the binary class version of our datasets, at the same time enabling the extraction of knowledge from ageing-related data using quantitative influence information.
Availability and Implementation: The datasets created in this paper will be freely available after publication.
Contact: ff79@kent.ac.uk
Supplementary information: Supplementary data are available at Bioinformatics online.
Statistical modeling of isoform splicing dynamics from RNA-seq time series data
Authors: Huang Yuanhua , Sanguinetti Guido 
Published: June 2016

Abstract
Motivation: Isoform quantification is an important goal of RNA-seq experiments, yet it remains problematic for genes with low expression or several isoforms. These difficulties may in principle be ameliorated by exploiting correlated experimental designs, such as time series or dosage response experiments. Time series RNA-seq experiments, in particular, are becoming increasingly popular, yet there are no methods that explicitly leverage the experimental design to improve isoform quantification.
Results: Here, we present DICEseq, the first isoform quantification method tailored to correlated RNA-seq experiments. DICEseq explicitly models the correlations between different RNA-seq experiments to aid the quantification of isoforms across experiments. Numerical experiments on simulated datasets show that DICEseq yields more accurate results than state-of-the-art methods, an advantage that can become considerable at low coverage levels. On real datasets, our results show that DICEseq provides substantially more reproducible and robust quantifications, increasing the correlation of estimates from replicate datasets by up to 10% on genes with low or moderate expression levels (bottom third of all genes). Furthermore, DICEseq permits to quantify the trade-off between temporal sampling of RNA and depth of sequencing, frequently an important choice when planning experiments. Our results have strong implications for the design of RNA-seq experiments, and offer a novel tool for improved analysis of such datasets.
Availability and Implementation: Python code is freely available at http://diceseq.sf.net.
Contact: G.Sanguinetti@ed.ac.uk
Supplementary information: Supplementary data are available at Bioinformatics online.
SELAM: simulation of epistasis and local adaptation during admixture with mate choice
Authors: Corbett-Detig Russell , Jones Matt 
Published: June 2016

Abstract
Summary: SELAM is a forward time population genetic simulation program that provides a flexible framework for simulating admixture between any number of ancestral populations. The program can be used to simulate complex demographic and selection models, including dioecious or monoecious populations, autosomal or sex chromosomes, local adaptation, dominance, epistasis, and mate choice.
Availability and Implementation: The SELAM package (C ++ source code, examples and manuals) is available via github at https://github.com/russcd/SELAM. This package is distributed under version 3 of the GNU general public license.
Contact: russcd@gmail.com
NegGOA: negative GO annotations selection using ontology structure
Authors: Fu Guangyuan , Wang Jun , Yang Bo , Yu Guoxian 
Published: June 2016

Abstract
Motivation: Predicting the biological functions of proteins is one of the key challenges in the post-genomic era. Computational models have demonstrated the utility of applying machine learning methods to predict protein function. Most prediction methods explicitly require a set of negative examples—proteins that are known not carrying out a particular function. However, Gene Ontology (GO) almost always only provides the knowledge that proteins carry out a particular function, and functional annotations of proteins are incomplete. GO structurally organizes more than tens of thousands GO terms and a protein is annotated with several (or dozens) of these terms. For these reasons, the negative examples of a protein can greatly help distinguishing true positive examples of the protein from such a large candidate GO space.
Results: In this paper, we present a novel approach (called NegGOA) to select negative examples. Specifically, NegGOA takes advantage of the ontology structure, available annotations and potentiality of additional annotations of a protein to choose negative examples of the protein. We compare NegGOA with other negative examples selection algorithms and find that NegGOA produces much fewer false negatives than them. We incorporate the selected negative examples into an efficient function prediction model to predict the functions of proteins in Yeast, Human, Mouse and Fly. NegGOA also demonstrates improved accuracy than these comparing algorithms across various evaluation metrics. In addition, NegGOA is less suffered from incomplete annotations of proteins than these comparing methods.
Availability and Implementation: The Matlab and R codes are available at https://sites.google.com/site/guoxian85/neggoa.
Contact: gxyu@swu.edu.cn
Supplementary information: Supplementary data are available at Bioinformatics online.
TADtool: visual parameter identification for TAD-calling algorithms
Authors: Kruse Kai , Hug Clemens B. , Hernández-Rodríguez Benjamín , Vaquerizas Juan M. 
Published: June 2016

Abstract
Summary: Eukaryotic genomes are hierarchically organized into topologically associating domains (TADs). The computational identification of these domains and their associated properties critically depends on the choice of suitable parameters of TAD-calling algorithms. To reduce the element of trial-and-error in parameter selection, we have developed TADtool: an interactive plot to find robust TAD-calling parameters with immediate visual feedback. TADtool allows the direct export of TADs called with a chosen set of parameters for two of the most common TAD calling algorithms: directionality and insulation index. It can be used as an intuitive, standalone application or as a Python package for maximum flexibility.
Availability and implementation: TADtool is available as a Python package from GitHub (https://github.com/vaquerizaslab/tadtool) or can be installed directly via PyPI, the Python package index (tadtool).
Contact: kai.kruse@mpi-muenster.mpg.de, jmv@mpi-muenster.mpg.de
Supplementary information: Supplementary data are available at Bioinformatics online.
Assemblytics: a web analytics tool for the detection of variants from an assembly
Authors: Nattestad Maria , Schatz Michael C. 
Published: June 2016

Abstract
Summary: Assemblytics is a web app for detecting and analyzing variants from a de novo genome assembly aligned to a reference genome. It incorporates a unique anchor filtering approach to increase robustness to repetitive elements, and identifies six classes of variants based on their distinct alignment signatures. Assemblytics can be applied both to comparing aberrant genomes, such as human cancers, to a reference, or to identify differences between related species. Multiple interactive visualizations enable in-depth explorations of the genomic distributions of variants.
Availability and Implementation: http://assemblytics.com, https://github.com/marianattestad/assemblytics
Contact: mnattest@cshl.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
Genome puzzle master (GPM): an integrated pipeline for building and editing pseudomolecules from fragmented sequences
Authors: Zhang Jianwei , Kudrna Dave , Mu Ting , Li Weiming , Copetti Dario , Yu Yeisoo , Goicoechea Jose Luis , Lei Yang , Wing Rod A. 
Published: June 2016

Abstract
Motivation: Next generation sequencing technologies have revolutionized our ability to rapidly and affordably generate vast quantities of sequence data. Once generated, raw sequences are assembled into contigs or scaffolds. However, these assemblies are mostly fragmented and inaccurate at the whole genome scale, largely due to the inability to integrate additional informative datasets (e.g. physical, optical and genetic maps). To address this problem, we developed a semi-automated software tool—Genome Puzzle Master (GPM)—that enables the integration of additional genomic signposts to edit and build ‘new-gen-assemblies’ that result in high-quality ‘annotation-ready’ pseudomolecules.
Results: With GPM, loaded datasets can be connected to each other via their logical relationships which accomplishes tasks to ‘group,’ ‘merge,’ ‘order and orient’ sequences in a draft assembly. Manual editing can also be performed with a user-friendly graphical interface. Final pseudomolecules reflect a user’s total data package and are available for long-term project management. GPM is a web-based pipeline and an important part of a Laboratory Information Management System (LIMS) which can be easily deployed on local servers for any genome research laboratory.
Availability and Implementation: The GPM (with LIMS) package is available at https://github.com/Jianwei-Zhang/LIMS
Contacts: jzhang@mail.hzau.edu.cn or rwing@mail.arizona.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
Pseudotime estimation: deconfounding single cell time series
Authors: Reid John E. , Wernisch Lorenz 
Published: June 2016

AbstractMotivation: Repeated cross-sectional time series single cell data confound several sources of variation, with contributions from measurement noise, stochastic cell-to-cell variation and cell progression at different rates. Time series from single cell assays are particularly susceptible to confounding as the measurements are not averaged over populations of cells. When several genes are assayed in parallel these effects can be estimated and corrected for under certain smoothness assumptions on cell progression.Results: We present a principled probabilistic model with a Bayesian inference scheme to analyse such data. We demonstrate our method’s utility on public microarray, nCounter and RNA-seq datasets from three organisms. Our method almost perfectly recovers withheld capture times in an Arabidopsis dataset, it accurately estimates cell cycle peak times in a human prostate cancer cell line and it correctly identifies two precocious cells in a study of paracrine signalling in mouse dendritic cells. Furthermore, our method compares favourably with Monocle, a state-of-the-art technique. We also show using held-out data that uncertainty in the temporal dimension is a common confounder and should be accounted for in analyses of repeated cross-sectional time series.Availability and Implementation: Our method is available on CRAN in the DeLorean package.Contact: john.reid@mrc-bsu.cam.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online.
PhenoScanner: a database of human genotype–phenotype associations
Authors: Staley James R. , Blackshaw James , Kamat Mihir A. , Ellis Steve , Surendran Praveen , Sun Benjamin B. , Paul Dirk S. , Freitag Daniel , Burgess Stephen , Danesh John , Young Robin , Butterworth Adam S. 
Published: June 2016

Abstract
Summary: PhenoScanner is a curated database of publicly available results from large-scale genetic association studies. This tool aims to facilitate ‘phenome scans’, the cross-referencing of genetic variants with many phenotypes, to help aid understanding of disease pathways and biology. The database currently contains over 350 million association results and over 10 million unique genetic variants, mostly single nucleotide polymorphisms. It is accompanied by a web-based tool that queries the database for associations with user-specified variants, providing results according to the same effect and non-effect alleles for each input variant. The tool provides the option of searching for trait associations with proxies of the input variants, calculated using the European samples from 1000 Genomes and Hapmap.
Availability and Implementation: PhenoScanner is available at www.phenoscanner.medschl.cam.ac.uk.
Contact: jrs95@medschl.cam.ac.uk
Supplementary information: Supplementary data are available at Bioinformatics online.
Maternal Human Immunodeficiency Virus-Associated Hypergammaglobulinemia Reduces Transplacental Transfer of Immunoglobulin G to Plasmodium falciparum Antigens in Cameroonian Neonates
Authors: Babakhanyan Anna , Ekali Gabriel Loni , Dent Arlene , Kazura James , Nguasong John Tamo , Fodjo Barriere Airy Yetgang , Yuosembom Emile Keming , Esemu Livo Forgu , Taylor Diane Wallace , Leke Rose Gana Fomban 
Published: June 2016

Abstract
Background.  Human immunodeficiency virus (HIV) infection reduces placental transfer of antibodies from mother to the fetus for many antigens; however, conflicting data exist for transfer of immunoglobulin G (IgG) to malarial antigens. The mechanism(s) underlying reduced placental transfer is unknown.
Methods.  Levels of maternal and cord total IgG, IgG subclasses, and cord-to-mother ratios (CMRs) were measured in 107 mother-cord pairs to 3 malarial antigens: circumsporozoite protein (CSP), apical membrane antigen 1 (AMA-1), merozoite surface protein 1 (MSP-1), and tetanus toxoid C-fragment (TTc).
Results.  Immunoglobulin G levels to CSP and TTc were lower in HIV+ mothers, and cord IgG to CSP, MSP-1, and TTc were significantly lower in neonates born to HIV+ mothers (all P values &lt;.05). The prevalence of mothers with hypergammaglobulinemia was significantly higher among HIV+ women (68%) compared with HIV− mothers (8%) (P &lt; .0001). Maternal hypergammaglobulinemia was associated with reduction in transplacental transfer of antibodies to CSP (P = .03), MSP-1 (P = .004), and TTc (P = .012), and CMRs &lt;1 were found for MSP-1 (odds ratio [OR] = 6.5), TTc (OR = 4.95), and IgG1 to CSP (OR = 3.75, P = .025) in statistical models adjusted for maternal IgG.
Conclusions.  Data confirmed that HIV infections are associated with lower cord antibody levels to malarial antigens and that hypergammaglobulinemia may contribute to reduced antibody transfer.
RSQ: a statistical method for quantification of isoform-specific structurome using transcriptome-wide structural profiling data
Authors: Wang Yunfei , Zhu Xiaopeng , Sun Ming , Chen Yong , Chen Yiwen , Tu Shikui , Bai Boyang , Chen Min , Dai Qi , Wang Haozhe , Zhang Michael Q. , Xuan Zhenyu 
Published: June 2016

AbstractThe structure of RNA, which is considered to be a second layer of information alongside the genetic code, provides fundamental insights into the cellular function of both coding and non-coding RNAs. Several high-throughput technologies have been developed to profile transcriptome-wide RNA structures, i.e., the structurome. However, it is challenging to interpret the profiling data because the observed data represent an average over different RNA conformations and isoforms with different abundance. To address this challenge, we developed an RNA structurome quantification method (RSQ) to statistically model the distribution of reads over both isoforms and RNA conformations, and thus provide accurate quantification of the isoform-specific structurome. The quantified RNA structurome enables the comparison of isoform-specific conformations between different conditions, the exploration of RNA conformation variation affected by single nucleotide polymorphism (SNP),and the measurement of RNA accessibility for binding of either small RNAs in RNAi-based assays or RNA binding protein in transcriptional regulation. The model used in our method sheds new light on the potential impact of the RNA structurome on gene regulation.
Higher stress and immunity responses are associated with higher mortality in reef-building coral exposed to a bacterial challenge
Authors: Wright Rachel M. , Kenkel Carly D. , Dunn Carly E. , Shilling Erin N. , Bay Line K. , Matz Mikhail V. 
Published: June 2016

ABSTRACTUnderstanding the drivers of intraspecific variation in susceptibility is essential to manage increasingly frequent coral disease outbreaks. We challenged replicate fragments of eight Acropora millepora genotypes with Vibrio spp. to quantify variation in lesion development and to identify host and coral-associated microbial community properties associated with resistance. While Vibrio spp. remained relatively rare in the microbiome of challenged corals, other stress-associated microbial taxa significantly increased in abundance. Contrary to expectations, higher constitutive immunity and more active immune responses did not confer higher resistance to bacterial challenge. Furthermore, more pronounced gene expression responses to bacterial challenge were associated with higher rather than lower mortality. A newly developed gene expression assay based on two genes related to inflammation and immune responses, deleted in malignant brain tumors 1 and a matrix metalloproteinase, predicted mortality under Vibrio treatment both in the initial experiment and in a validation experiment involving another 20 A. millepora genotypes. Instead of mounting more robust responses, resistant corals were largely unaffected by the bacterial challenge and maintained gene expression signatures of healthier condition, including elevated fluorescent proteins and ribosomal biosynthesis along with diminished ubiquitination. Overall, our results support the view that coral disease and mortality is commonly due to opportunistic pathogens exploiting physiologically compromised hosts rather than specific infections, and show, contrary to the prevailing wisdom, that greater immune responses do not necessarily translate into greater disease resistance.
Complex admixture preceded and followed the extinction of wisent in the wild
Authors: Węcek Karolina , Hartmann Stefanie , Paijmans Johanna L. A. , Taron Ulrike , Xenikoudakis Georgios , Cahill James A. , Heintzman Peter D. , Shapiro Beth , Baryshnikov Gennady , Bunevich Aleksei N. , Crees Jennifer J. , Dobosz Roland , Manaserian Ninna , Okarma Henryk , Tokarska Małgorzata , Turvey Samuel T. , Wójcik Jan M. , Żyła Waldemar , Szymura Jacek M. , Hofreiter Michael , Barlow Axel 
Published: June 2016

AbstractRetracing complex population processes that precede extreme bottlenecks may be impossible using data from living individuals. The wisent (Bison bonasus), Europe’s largest terrestrial mammal, exemplifies such a population history, having gone extinct in the wild but subsequently restored by captive breeding efforts. Using low coverage genomic data from modern and historical individuals, we investigate population processes occurring before and after this extinction. Analysis of aligned genomes supports the division of wisent into two previously recognised subspecies, but almost half of the genomic alignment contradicts this population history as a result of incomplete lineage sorting and admixture. Admixture between subspecies populations occurred prior to extinction and subsequently during the captive breeding program. Admixture with theBoscattle lineage is also widespread but results from ancient events rather than recent hybridisation with domestics. Our study demonstrates the huge potential of historical genomes for both studying evolutionary histories and for guiding conservation strategies.
The genetics of an early Neolithic pastoralist from the Zagros, Iran
Authors: Gallego-Llorente M. , Connell S. , Jones E. R. , Merrett D. C. , Jeon Y. , Eriksson A. , Siska V. , Gamba C. , Meiklejohn C. , Beyer R. , Jeon S. , Cho Y. S. , Hofreiter M. , Bhak J. , Manica A. , Pinhasi R. 
Published: June 2016

AbstractThe agricultural transition profoundly changed human societies. We sequenced and analysed the first genome (1.39×) of an early Neolithic woman from Ganj Dareh, in the Zagros Mountains of Iran, a site with early evidence for an economy based on goat herding,ca. 10,000 BP. We show that Western Iran was inhabited by a population genetically most similar to hunter-gatherers from the Caucasus, but distinct from the Neolithic Anatolian people who later brought food production into Europe. The inhabitants of Ganj Dareh made little direct genetic contribution to modern European populations, suggesting they were somewhat isolated from other populations in the region. Runs of homozygosity are of a similar length to those from Neolithic Anatolians, and shorter than those of Caucasus and Western Hunter-Gatherers, suggesting that the inhabitants of Ganj Dareh did not undergo the large population bottleneck suffered by their northern neighbours. While some degree of cultural diffusion between Anatolia, Western Iran and other neighbouring regions is possible, the genetic dissimilarity of early Anatolian farmers and the inhabitants of Ganj Dareh supports a model in which Neolithic societies in these areas were distinct.