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https://www.readbyqxmd.com/read/27895194/systematic-characterization-and-prediction-of-human-hypertension-genes
#1
Yan-Hui Li, Gai-Gai Zhang, Nanping Wang
Hypertension is a major cardiovascular risk factor and accounts for a large part of cardiovascular mortality. In this work, we analyzed the properties of hypertension genes and found that when compared with genes not yet known to be involved in hypertension regulation, known hypertension genes display distinguishing features: (1) hypertension genes tend to be located at network center; (2) hypertension genes tend to interact with each other; and (3) hypertension genes tend to enrich in certain biological processes and show certain phenotypes...
November 28, 2016: Hypertension
https://www.readbyqxmd.com/read/27881783/multivariate-brain-prediction-of-heart-rate-and-skin-conductance-responses-to-social-threat
#2
Hedwig Eisenbarth, Luke J Chang, Tor D Wager
: Psychosocial stressors induce autonomic nervous system (ANS) responses in multiple body systems that are linked to health risks. Much work has focused on the common effects of stress, but ANS responses in different body systems are dissociable and may result from distinct patterns of cortical-subcortical interactions. Here, we used machine learning to develop multivariate patterns of fMRI activity predictive of heart rate (HR) and skin conductance level (SCL) responses during social threat in humans (N = 18)...
November 23, 2016: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/27875301/an-intrinsically-disordered-aplf-links-ku-dna-pkcs-and-xrcc4-dna-ligase-iv-in-an-extended-flexible-non-homologous-end-joining-complex
#3
Michal Hammel, Yaping Yu, Sarvan Kumar Radhakrishnan, Chirayu Chokshi, Miaw-Sheue Tsai, Yoshihiro Matsumoto, Monica Kuzdovich, Soumya G Remesh, Shujuan Fang, Alan E Tomkinson, Susan P Lees-Miller, John A Tainer
DNA double-strand break (DSB) repair by non-homologous end joining (NHEJ) in human cells is initiated by Ku heterodimer binding to a DSB, followed by recruitment of core NHEJ factors including DNA-dependent protein kinase catalytic subunit (DNA-PKcs), XRCC4-like factor (XLF) and XRCC4 (X4)-DNA ligase IV (L4). In addition, Ku interacts with accessory factors such as Aprataxin and Polynucleotide kinase/phosphatase-Like Factor (APLF), yet how these factors interact to tether, process and ligate DSB ends while allowing regulation and chromatin interactions remains enigmatic...
November 14, 2016: Journal of Biological Chemistry
https://www.readbyqxmd.com/read/27875141/visual-interaction-with-dimensionality-reduction-a-structured-literature-analysis
#4
Dominik Sacha, Leishi Zhang, Michael Sedlmair, John A Lee, Jaakko Peltonen, Daniel Weiskopf, Stephen C North, Daniel A Keim
Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data. For DR techniques to be useful in exploratory data analysis, they need to be adapted to human needs and domain-specific problems, ideally, interactively, and on-the-fly. Many visual analytics systems have already demonstrated the benefits of tightly integrating DR with interactive visualizations. Nevertheless, a general, structured understanding of this integration is missing. To address this, we systematically studied the visual analytics and visualization literature to investigate how analysts interact with automatic DR techniques...
January 2017: IEEE Transactions on Visualization and Computer Graphics
https://www.readbyqxmd.com/read/27867351/advice-taking-from-humans-and-machines-an-fmri-and-effective-connectivity-study
#5
Kimberly Goodyear, Raja Parasuraman, Sergey Chernyak, Poornima Madhavan, Gopikrishna Deshpande, Frank Krueger
With new technological advances, advice can come from different sources such as machines or humans, but how individuals respond to such advice and the neural correlates involved need to be better understood. We combined functional MRI and multivariate Granger causality analysis with an X-ray luggage-screening task to investigate the neural basis and corresponding effective connectivity involved with advice utilization from agents framed as experts. Participants were asked to accept or reject good or bad advice from a human or machine agent with low reliability (high false alarm rate)...
2016: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/27864674/interactions-between-giardia-duodenalis-sm-proteins-and-their-association-with-spliceosomal-snrnas
#6
Vanessa Gómez, Moisés Wasserman
Giardia duodenalis is a parasite that colonises the intestines of humans and other vertebrates, causing diarrhoea and poor nutrient absorption. G. duodenalis is sometimes considered an early diverging eukaryote, and its genome exhibits simplified molecular machinery for many cellular processes, which makes it an interesting model to study. The spliceosome, one of the most complex molecular machines in the eukaryotic cell, is responsible for intron excision and exon splicing. Just over a decade ago, it was believed that the G...
November 18, 2016: Parasitology Research
https://www.readbyqxmd.com/read/27861505/content-based-discovery-for-web-map-service-using-support-vector-machine-and-user-relevance-feedback
#7
Kai Hu, Zhipeng Gui, Xiaoqiang Cheng, Kunlun Qi, Jie Zheng, Lan You, Huayi Wu
Many discovery methods for geographic information services have been proposed. There are approaches for finding and matching geographic information services, methods for constructing geographic information service classification schemes, and automatic geographic information discovery. Overall, the efficiency of the geographic information discovery keeps improving., There are however, still two problems in Web Map Service (WMS) discovery that must be solved. Mismatches between the graphic contents of a WMS and the semantic descriptions in the metadata make discovery difficult for human users...
2016: PloS One
https://www.readbyqxmd.com/read/27849060/large-scale-identification-of-human-protein-function-using-topological-features-of-interaction-network
#8
Zhanchao Li, Zhiqing Liu, Wenqian Zhong, Menghua Huang, Na Wu, Yun Xie, Zong Dai, Xiaoyong Zou
The annotation of protein function is a vital step to elucidate the essence of life at a molecular level, and it is also meritorious in biomedical and pharmaceutical industry. Developments of sequencing technology result in constant expansion of the gap between the number of the known sequences and their functions. Therefore, it is indispensable to develop a computational method for the annotation of protein function. Herein, a novel method is proposed to identify protein function based on the weighted human protein-protein interaction network and graph theory...
November 16, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27845677/multimodal-feature-based-surface-material-classification
#9
Matti Strese, Clemens Schuwerk, Albert Iepure, Eckehard Steinbach
When a tool is tapped on or dragged over an object surface, vibrations are induced in the tool, which can be captured using acceleration sensors. The tool-surface interaction additionally creates audible sound waves, which can be recorded using microphones. Features extracted from camera images provide additional information about the surfaces. We present an approach for tool-mediated surface classification that combines these signals and demonstrate that the proposed method is robust against variable scan-time parameters...
November 7, 2016: IEEE Transactions on Haptics
https://www.readbyqxmd.com/read/27842491/feature-based-classification-of-human-transcription-factors-into-hypothetical-sub-classes-related-to-regulatory-function
#10
Rezvan Ehsani, Shahram Bahrami, Finn Drabløs
BACKGROUND: Transcription factors are key proteins in the regulation of gene transcription. An important step in this process is the opening of chromatin in order to make genomic regions available for transcription. Data on DNase I hypersensitivity has previously been used to label a subset of transcription factors as Pioneers, Settlers and Migrants to describe their potential role in this process. These labels represent an interesting hypothesis on gene regulation and possibly a useful approach for data analysis, and therefore we wanted to expand the set of labeled transcription factors to include as many known factors as possible...
November 14, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/27814491/nbs1-converts-the-human-mre11-rad50-nuclease-complex-into-an-endo-exonuclease-machine-specific-for-protein-dna-adducts
#11
Rajashree A Deshpande, Ji-Hoon Lee, Sucheta Arora, Tanya T Paull
The human Mre11/Rad50/Nbs1 (hMRN) complex is critical for the sensing, processing, and signaling of DNA double-strand breaks. The nuclease activity of Mre11 is essential for mammalian development and cell viability, although the regulation and substrate specificity of Mre11 have been difficult to define. Here we show that hMRN catalyzes sequential endonucleolytic and exonucleolytic activities on both 5' and 3' strands of DNA ends containing protein adducts, and that Nbs1, ATP, and adducts are essential for this function...
November 3, 2016: Molecular Cell
https://www.readbyqxmd.com/read/27812193/the-modular-adaptive-ribosome
#12
Anupama Yadav, Aparna Radhakrishnan, Anshuman Panda, Amartya Singh, Himanshu Sinha, Gyan Bhanot
The ribosome is an ancient machine, performing the same function across organisms. Although functionally unitary, recent experiments suggest specialized roles for some ribosomal proteins. Our central thesis is that ribosomal proteins function in a modular fashion to decode genetic information in a context dependent manner. We show through large data analyses that although many ribosomal proteins are essential with consistent effect on growth in different conditions in yeast and similar expression across cell and tissue types in mice and humans, some ribosomal proteins are used in an environment specific manner...
2016: PloS One
https://www.readbyqxmd.com/read/27812085/wormhole-novel-least-diverged-ortholog-prediction-through-machine-learning
#13
George L Sutphin, J Matthew Mahoney, Keith Sheppard, David O Walton, Ron Korstanje
The rapid advancement of technology in genomics and targeted genetic manipulation has made comparative biology an increasingly prominent strategy to model human disease processes. Predicting orthology relationships between species is a vital component of comparative biology. Dozens of strategies for predicting orthologs have been developed using combinations of gene and protein sequence, phylogenetic history, and functional interaction with progressively increasing accuracy. A relatively new class of orthology prediction strategies combines aspects of multiple methods into meta-tools, resulting in improved prediction performance...
November 2016: PLoS Computational Biology
https://www.readbyqxmd.com/read/27806121/fully-automated-enhanced-tumor-compartmentalization-man-vs-machine-reloaded
#14
Nicole Porz, Simon Habegger, Raphael Meier, Rajeev Verma, Astrid Jilch, Jens Fichtner, Urspeter Knecht, Christian Radina, Philippe Schucht, Jürgen Beck, Andreas Raabe, Johannes Slotboom, Mauricio Reyes, Roland Wiest
OBJECTIVE: Comparison of a fully-automated segmentation method that uses compartmental volume information to a semi-automatic user-guided and FDA-approved segmentation technique. METHODS: Nineteen patients with a recently diagnosed and histologically confirmed glioblastoma (GBM) were included and MR images were acquired with a 1.5 T MR scanner. Manual segmentation for volumetric analyses was performed using the open source software 3D Slicer version 4.2.2.3 (www...
2016: PloS One
https://www.readbyqxmd.com/read/27784204/evaluation-of-molecular-brain-changes-associated-with-environmental-stress-in-rodent-models-compared-to-human-major-depressive-disorder-a-proteomic-systems-approach
#15
David Alan Cox, Michael Gerd Gottschalk, Viktoria Stelzhammer, Hendrik Wesseling, Jason David Cooper, Sabine Bahn
OBJECTIVES: Rodent models of major depressive disorder (MDD) are indispensable when screening for novel treatments, but assessing their translational relevance with human brain pathology has proved difficult. METHODS: Using a novel systems approach, proteomics data obtained from post-mortem MDD anterior prefrontal cortex tissue (n =12) and matched controls (n = 23) were compared with equivalent data from three commonly used preclinical models exposed to environmental stressors (chronic mild stress, prenatal stress, social defeat)...
October 27, 2016: World Journal of Biological Psychiatry
https://www.readbyqxmd.com/read/27766844/one-piece-triboelectric-nanosensor-for-self-triggered-alarm-system-and-latent-fingerprint-detection
#16
Yang Jie, Huarui Zhu, Xia Cao, Yue Zhang, Ning Wang, Liqun Zhang, Zhong Lin Wang
Tactile sensing is of great importance in developing human-machine interface, remote control and security systems. Here, a self-triggered alarm system based on the one-piece triboelectric nanosensor (TENS) is reported. By using nitrocellulose (NC) membrane as the triboelectric material, the as-designed TENS can not only sensitively respond to physical contacts in a self-triggered mode, but also securely detect the third-level details of latent fingerprint. The self-triggered idea based on the triboelectric nanogenerator is compatible with intelligent interactive interface...
October 21, 2016: ACS Nano
https://www.readbyqxmd.com/read/27759121/robust-and-accurate-prediction-of-protein-self-interactions-from-amino-acids-sequence-using-evolutionary-information
#17
Ji-Yong An, Zhu-Hong You, Xing Chen, De-Shuang Huang, Guiying Yan, Da-Fu Wang
Self-interacting proteins (SIPs) play an essential role in cellular functions and the evolution of protein interaction networks (PINs). Due to the limitations of experimental self-interaction proteins detection technology, it is a very important task to develop a robust and accurate computational approach for SIPs prediction. In this study, we propose a novel computational method for predicting SIPs from protein amino acids sequence. Firstly, a novel feature representation scheme based on Local Binary Pattern (LBP) is developed, in which the evolutionary information, in the form of multiple sequence alignments, is taken into account...
October 19, 2016: Molecular BioSystems
https://www.readbyqxmd.com/read/27757060/omics-approaches-to-individual-variation-modeling-networks-and-the-virtual-patient
#18
Hans Lehrach
Every human is unique. We differ in our genomes, environment, behavior, disease history, and past and current medical treatment-a complex catalog of differences that often leads to variations in the way each of us responds to a particular therapy. We argue here that true personalization of drug therapies will rely on "virtual patient" models based on a detailed characterization of the individual patient by molecular, imaging, and sensor techniques. The models will be based, wherever possible, on the molecular mechanisms of disease processes and drug action but can also expand to hybrid models including statistics/machine learning/artificial intelligence-based elements trained on available data to address therapeutic areas or therapies for which insufficient information on mechanisms is available...
September 2016: Dialogues in Clinical Neuroscience
https://www.readbyqxmd.com/read/27750433/the-novel-landscape-of-long-non-coding-rnas-in-response-to-human-foamy-virus-infection-characterized-by-rna-seq
#19
Shanshan Xu, Lanlan Dong, Yingying Shi, Liujun Chen, Peipei Yuan, Shuang Wang, Zhi Li, Yan Sun, Song Han, Jun Yin, Biwen Peng, Xiaohua He, Wanhong Liu
Human foamy virus (HFV) is a complex and unique retrovirus with the longest genomes among retroviruses used as vectors for gene therapy. Long non-coding RNAs (lncRNAs) are regarded as key regulators that involved in diverse biological processes during viral infection. However, the role of lncRNAs in HFV infection remains unknown. In this study, we utilized next-generation sequencing to first characterize lncRNAs in 293T cells after HFV infection, evaluating length distribution, exon number distribution, volcano picture and lncRNA class distribution...
October 18, 2016: AIDS Research and Human Retroviruses
https://www.readbyqxmd.com/read/27747607/interactive-machine-learning-for-health-informatics-when-do-we-need-the-human-in-the-loop
#20
Andreas Holzinger
Machine learning (ML) is the fastest growing field in computer science, and health informatics is among the greatest challenges. The goal of ML is to develop algorithms which can learn and improve over time and can be used for predictions. Most ML researchers concentrate on automatic machine learning (aML), where great advances have been made, for example, in speech recognition, recommender systems, or autonomous vehicles. Automatic approaches greatly benefit from big data with many training sets. However, in the health domain, sometimes we are confronted with a small number of data sets or rare events, where aML-approaches suffer of insufficient training samples...
June 2016: Brain Informatics
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