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https://www.readbyqxmd.com/read/29029323/lncrnal20992-regulates-apoptotic-proteins-to-promote-lead-induced-neuronal-apoptosis
#1
Aruo Nan, Yangyang Jia, Xin Li, Meiling Liu, Nan Zhang, Lijian Chen, Ti Yang, Yiqin Xu, Xin Dai, Ying Cheng, Zhenzhong Liu, Yihui Ling, Yiguo Jiang
Lead is a heavy metal pollutant that is widely present in the environment and can seriously harm human health, especially the nervous system. Long noncoding RNAs (lncRNAs) play important roles in many physiological and pathological processes; however, there remains a lack of in-depth studies on the molecular mechanisms associated with lead neurotoxicity. Here, our results showed that lead exposure inhibited cell proliferation and promoted cell apoptosis. We observed that lncRNAL20992 was significantly upregulated in a lead-induced neuronal-injury cell model according to quantitative reverse transcription polymerase chain reaction...
September 25, 2017: Toxicological Sciences: An Official Journal of the Society of Toxicology
https://www.readbyqxmd.com/read/29029172/dnasp-6-dna-sequence-polymorphism-analysis-of-large-datasets
#2
Julio Rozas, Albert Ferrer-Mata, Juan Carlos Sánchez-DelBarrio, Sara Guirao-Rico, Pablo Librado, Sebastián E Ramos-Onsins, Alejandro Sánchez-Gracia
We present version 6 of the DnaSP (DNA Sequence Polymorphism) software, a new version of the popular tool for performing exhaustive population genetic analyses on multiple sequence alignments. This major upgrade incorporates novel functionalities to analyse large datasets, such as those generated by high-throughput sequencing (HTS) technologies. Among other features, DnaSP 6 implements: i) modules for reading and analysing data from genomic partitioning methods, such as RADseq or hybrid enrichment approaches, ii) faster methods scalable for HTS data, and iii) summary statistics for the analysis of multi-locus population genetics data...
September 18, 2017: Molecular Biology and Evolution
https://www.readbyqxmd.com/read/29029016/an-r-package-to-compute-diffusion-based-scores-on-biological-networks-diffustats
#3
Sergio Picart-Armada, Wesley K Thompson, Alfonso Buil, Alexandre Perera-Lluna
Summary: Label propagation and diffusion over biological networks are a common mathematical formalism in computational biology for giving context to molecular entities and prioritising novel candidates in the area of study. There are several choices in conceiving the diffusion process -involving the graph kernel, the score definitions and the presence of a posterior statistical normalisation- which have an impact on the results. This manuscript describes diffuStats, an R package that provides a collection of graph kernels and diffusion scores, as well as a parallel permutation analysis for the normalised scores, that eases the computation of the scores and their benchmarking for an optimal choice...
October 5, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028988/quasar-mpra-accurate-allele-specific-analysis-for-massively-parallel-reporter-assays
#4
Cynthia A Kalita, Gregory A Moyerbrailean, Christopher Brown, Xiaoquan Wen, Francesca Luca, Roger Pique-Regi
Motivation: The majority of the human genome is composed of non-coding regions containing regulatory elements such as enhancers, which are crucial for controlling gene expression. Many variants associated with complex traits are in these regions, and may disrupt gene regulatory sequences. Consequently, it is important to not only identify true enhancers but also to test if a variant within an enhancer affects gene regulation. Recently, allele-specific analysis in high-throughput reporter assays, such as massively parallel reporter assays (MPRA), have been used to functionally validate non-coding variants...
September 22, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028982/trove-a-user-friendly-tool-for-visualizing-and-analyzing-cancer-hallmarks-in-signaling-networks
#5
Huey Eng Chua, Sourav S Bhowmick, Jie Zheng
Summary: Cancer hallmarks, a concept that seeks to explain the complexity of cancer initiation and development, provide a new perspective of studying cancer signaling which could lead to a greater understanding of this complex disease. However, to the best of our knowledge, there is currently a lack of tools that support such hallmark-based study of the cancer signaling network, thereby impeding the gain of knowledge in this area. We present TROVE, a user-friendly software that facilitates hallmark annotation, visualization and analysis in cancer signaling networks...
September 22, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028963/zcchc17-is-a-master-regulator-of-synaptic-gene-expression-in-alzheimer-s-disease
#6
Zeljko Tomljanovic, Mitesh Patel, William Shin, Andrea Califano, Andrew F Teich
Motivation: In an effort to better understand the molecular drivers of synaptic and neurophysiologic dysfunction in Alzheimer's disease (AD), we analyzed neuronal gene expression data from human AD brain tissue to identify master regulators of synaptic gene expression. Results: Master regulator analysis identifies ZCCHC17 as normally supporting the expression of a network of synaptic genes, and predicts that ZCCHC17 dysfunction in AD leads to lower expression of these genes...
September 25, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028931/deepgo-predicting-protein-functions-from-sequence-and-interactions-using-a-deep-ontology-aware-classifier
#7
Maxat Kulmanov, Mohammed Asif Khan, Robert Hoehndorf
Motivation: A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40,000 classes...
September 28, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028926/structure-based-prediction-of-protein-peptide-binding-regions-using-random-forest
#8
Ghazaleh Taherzadeh, Yaoqi Zhou, Alan Wee-Chung Liew, Yuedong Yang
Motivation: Protein-peptide interactions are one of the most important biological interactions and play crucial role in many diseases including cancer. Therefore, knowledge of these interactions provides invaluable insights into all cellular processes, functional mechanisms, and drug discovery. Protein-peptide interactions can be analyzed by studying the structures of protein-peptide complexes. However, only a small portion has known complex structures and experimental determination of protein-peptide interaction is costly and inefficient...
September 26, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028911/genome-wide-pre-mirna-discovery-from-few-labeled-examples
#9
C Yones, G Stegmayer, D H Milone
Motivation: Although many machine learning techniques have been proposed for distinguishing miRNA hairpins from other stem-loop sequences, most of the current methods use supervised learning, which requires a very good set of positive and negative examples. Those methods have important practical limitations when they have to be applied to a real prediction task. First, there is the challenge of dealing with a scarce number of positive (well-known) pre-miRNA examples. Secondly, it is very difficult to build a good set of negative examples for representing the full spectrum of non-miRNA sequences...
September 25, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028909/the-systematic-analysis-of-ultraconserved-genomic-regions-in-the-budding-yeast
#10
Zhi-Kai Yang, Feng Gao
Motivation: In the evolution of species, a kind of special sequences, termed ultraconserved sequences (UCSs), have been inherited without any change, which strongly suggests those sequences should be crucial for the species to survive or adapt to the environment. However, the UCSs are still regarded as mysterious genetic sequences so far. Here, we present a systematic study of ultraconserved genomic regions in the budding yeast based on the publicly available genome sequences, in order to reveal their relationship with the adaptability or fitness advantages of the budding yeast...
September 27, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028907/oncomir-an-online-resource-for-exploring-pan-cancer-microrna-dysregulation
#11
Nathan W Wong, Yuhao Chen, Shuai Chen, Xiaowei Wang
Summary: Dysregulation of microRNAs (miRNAs) is extensively associated with cancer development and progression. miRNAs have been shown to be biomarkers for predicting tumor formation and outcome. However, identification of the relationships between miRNA expression and tumor characteristics can be difficult and time-consuming without appropriate bioinformatics expertise. To address this issue, we present OncomiR, an online resource for exploring miRNA dysregulation in cancer. Using combined miRNA-seq, RNA-seq, and clinical data from The Cancer Genome Atlas, we systematically performed statistical analyses to identify dysregulated miRNAs that are associated with tumor development and progression in most major cancer types...
October 3, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028906/critical-assessment-and-performance-improvement-of-plant-pathogen-protein-protein-interaction-prediction-methods
#12
Shiping Yang, Hong Li, Huaqin He, Yuan Zhou, Ziding Zhang
The identification of plant-pathogen protein-protein interactions (PPIs) is an attractive and challenging research topic for deciphering the complex molecular mechanism of plant immunity and pathogen infection. Considering that the experimental identification of plant-pathogen PPIs is time-consuming and labor-intensive, computational methods are emerging as an important strategy to complement the experimental methods. In this work, we first evaluated the performance of traditional computational methods such as interolog, domain-domain interaction and domain-motif interaction in predicting known plant-pathogen PPIs...
September 27, 2017: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29028898/diffloop-a-computational-framework-for-identifying-and-analyzing-differential-dna-loops-from-sequencing-data
#13
Caleb A Lareau, Martin J Aryee
Summary: The three-dimensional architecture of DNA within the nucleus is a key determinant of interactions between genes, regulatory elements, and transcriptional machinery. As a result, differences in DNA looping structure are associated with variation in gene expression and cell state. To systematically assess changes in DNA looping architecture between samples, we introduce diffloop, an R/Bioconductor package that provides a suite of functions for the quality control, statistical testing, annotation, and visualization of DNA loops...
September 29, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028897/sipros-ensemble-improves-database-searching-and-filtering-for-complex-metaproteomics
#14
Xuan Guo, Zhou Li, Qiuming Yao, Ryan S Mueller, Jimmy K Eng, David L Tabb, William Judson Hervey, Chongle Pan
Motivation: Complex microbial communities can be characterized by metagenomics and metaproteomics. However, metagenome assemblies often generate enormous, and yet incomplete, protein databases, which undermines the identification of peptides and proteins in metaproteomics. This challenge calls for increased discrimination of true identifications from false identifications by database searching and filtering algorithms in metaproteomics. Results: Sipros Ensemble was developed here for metaproteomics using an ensemble approach...
September 22, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028896/pydream-high-dimensional-parameter-inference-for-biological-models-in-python
#15
Erin M Shockley, Jasper A Vrugt, Carlos F Lopez
Summary: Biological models contain many parameters whose values are difficult to measure directly via experimentation and therefore require calibration against experimental data. Markov chain Monte Carlo (MCMC) methods are suitable to estimate multivariate posterior model parameter distributions, but these methods may exhibit slow or premature convergence in high-dimensional search spaces. Here, we present PyDREAM, a Python implementation of the (Multiple-Try) Differential Evolution Adaptive Metropolis (DREAM(ZS)) algorithm developed by Vrugt and ter Braak (2008) and Laloy and Vrugt (2012)...
October 4, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028895/ccmir-a-computational-approach-for-competitive-and-cooperative-microrna-binding-prediction
#16
Jun Ding, Xiaoman Li, Haiyan Hu
Motivation: The identification of microRNA (miRNA) target sites is important. In the past decade, dozens of computational methods have been developed to predict miRNA target sites. Despite their existence, rarely does a method consider the well-known competition and cooperation among miRNAs when attempts to discover target sites. To fill this gap, we developed a new approach called CCmiR, which takes the cooperation and competition of multiple miRNAs into account in a statistical model to predict their target sites...
September 25, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028891/on-the-mechanisms-of-protein-interactions-predicting-their-affinity-from-unbound-tertiary-structures
#17
Manuel Alejandro Marín-López, Joan Planas-Iglesias, Joaquim Aguirre-Plans, Jaume Bonet, Javier Garcia-Garcia, Narcis Fernandez-Fuentes, Baldo Oliva
Motivation: The characterization of the protein-protein association mechanisms is crucial to understanding how biological processes occur. It has been previously shown that the early formation of non-specific encounters enhances the realization of the stereospecific (i.e. native) complex by reducing the dimensionality of the search process. The association rate for the formation of such complex plays a crucial role in the cell biology and depends on how the partners diffuse to be close to each other...
September 27, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028888/rrdb-a-comprehensive-and-nonredundant-benchmark-for-rna-rna-docking-and-scoring
#18
Yumeng Yan, Sheng-You Huang
Motivation: With the discovery of more and more noncoding RNAs and their versatile functions, RNA-RNA interactions have received increased attention. Therefore, determination of their complex structures is valuable to understand the molecular mechanism of the interactions. Given the high cost of experimental methods, computational approaches like molecular docking have played an important role in the determination of complex structures, in which a benchmark is critical for the development of docking algorithms...
September 25, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028885/hotresdb-host-transcriptional-response-database-for-viral-hemorrhagic-fevers
#19
Jonathan Lo, Deric Zhang, Emily Speranza, Jose A Negron, John H Connor
Summary: High-throughput screening of the host transcriptional response to various viral infections provides a wealth of data but utilization of microarray and next generation sequencing (NGS) data for analysis can be difficult. The Host Transcriptional Response DataBase (HoTResDB), allows visitors to access already processed microarray and NGS data from non-human primate models of viral hemorrhagic fever to better understand the host transcriptional response. Availability: HoTResDB is freely available at http://hotresdb...
September 22, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028881/snp-genotyping-and-parameter-estimation-in-polyploids-using-low-coverage-sequencing-data
#20
Paul D Blischak, Laura S Kubatko, Andrea D Wolfe
Motivation: Genotyping and parameter estimation using high throughput sequencing data are everyday tasks for population geneticists, but methods developed for diploids are typically not applicable to polyploid taxa. This is due to their duplicated chromosomes, as well as the complex patterns of allelic exchange that often accompany whole genome duplication (WGD) events. For WGDs within a single lineage (autopolyploids), inbreeding can result from mixed mating and/or double reduction. For WGDs that involve hybridization (allopolyploids), alleles are typically inherited through independently segregating subgenomes...
September 22, 2017: Bioinformatics
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