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https://www.readbyqxmd.com/read/28514151/deepppi-boosting-prediction-of-protein-protein-interactions-with-deep-neural-networks
#1
Xiuquan Du, Shiwei Sun, Changlin Hu, Yu Yao, Yuanting Yan, Yanping Zhang
The complex language of eukaryotic gene expression remains incompletely understood. Despite the importance suggested by many proteins variants statistically associated with human disease, nearly all such variants have unknown mechanisms, for example, protein-protein interactions (PPIs). In this study, we address this challenge using a recent machine learning advance-deep neural networks (DNNs). We aim at improving the performance of PPIs prediction and propose a method called DeepPPI (Deep neural networks for Protein-Protein Interactions prediction), which employs deep neural networks to effectively learn the representations of proteins from common protein descriptors...
May 17, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28509865/detecting-and-classifying-human-touches-in-a-social-robot-through-acoustic-sensing-and-machine-learning
#2
Fernando Alonso-Martín, Juan José Gamboa-Montero, José Carlos Castillo, Álvaro Castro-González, Miguel Ángel Salichs
An important aspect in Human-Robot Interaction is responding to different kinds of touch stimuli. To date, several technologies have been explored to determine how a touch is perceived by a social robot, usually placing a large number of sensors throughout the robot's shell. In this work, we introduce a novel approach, where the audio acquired from contact microphones located in the robot's shell is processed using machine learning techniques to distinguish between different types of touches. The system is able to determine when the robot is touched (touch detection), and to ascertain the kind of touch performed among a set of possibilities: stroke, tap, slap, and tickle (touch classification)...
May 16, 2017: Sensors
https://www.readbyqxmd.com/read/28500008/wearable-haptic-systems-for-the-fingertip-and-the-hand-taxonomy-review-and-perspectives
#3
Claudio Pacchierotti, Stephen Sinclair, Massimiliano Solazzi, Antonio Frisoli, Vincent Hayward, Domenico Prattichizzo
In the last decade, we have witnessed a drastic change in the form factor of audio and vision technologies, from heavy and grounded machines to lightweight devices that naturally fit our bodies. However, only recently, haptic systems have started to be designed with wearability in mind. The wearability of haptic systems enables novel forms of communication, cooperation, and integration between humans and machines. Wearable haptic interfaces are capable of communicating with the human wearers during their interaction with the environment they share, in a natural and yet private way...
May 9, 2017: IEEE Transactions on Haptics
https://www.readbyqxmd.com/read/28499419/across-proteome-modeling-of-dimer-structures-for-the-bottom-up-assembly-of-protein-protein-interaction-networks
#4
Surabhi Maheshwari, Michal Brylinski
BACKGROUND: Deciphering complete networks of interactions between proteins is the key to comprehend cellular regulatory mechanisms. A significant effort has been devoted to expanding the coverage of the proteome-wide interaction space at molecular level. Although a growing body of research shows that protein docking can, in principle, be used to predict biologically relevant interactions, the accuracy of the across-proteome identification of interacting partners and the selection of near-native complex structures still need to be improved...
May 12, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28494725/computational-methods-for-predicting-ncrna-protein-interactions
#5
Shao-Wu Zhang, Xiao-Nan Fan
BACKGROUND: RNA-protein interactions (RPIs) play an important role in many cellular processes. In particular, noncoding RNA-protein interactions (ncRPIs) are involved in various gene regulations and human complex diseases. High-throughput experiments have provided a large number of valuable information about ncRPIs, but these experiments are expensive and time-consuming. Therefore, some computational approaches have been developed to predict ncRPIs efficiently and effectively. METHODS: In this work, we will describe the recent advance of predicting ncRPIs from the following aspects: i) the dataset construction; ii) the sequence and structural feature representation, and iii) the machine learning algorithm...
May 9, 2017: Medicinal Chemistry
https://www.readbyqxmd.com/read/28487265/effective-information-extraction-framework-for-heterogeneous-clinical-reports-using-online-machine-learning-and-controlled-vocabularies
#6
Shuai Zheng, James J Lu, Nima Ghasemzadeh, Salim S Hayek, Arshed A Quyyumi, Fusheng Wang
BACKGROUND: Extracting structured data from narrated medical reports is challenged by the complexity of heterogeneous structures and vocabularies and often requires significant manual effort. Traditional machine-based approaches lack the capability to take user feedbacks for improving the extraction algorithm in real time. OBJECTIVE: Our goal was to provide a generic information extraction framework that can support diverse clinical reports and enables a dynamic interaction between a human and a machine that produces highly accurate results...
May 9, 2017: JMIR Medical Informatics
https://www.readbyqxmd.com/read/28472232/privacy-preserving-evaporative-cooling-feature-selection-and-classification-with-relief-f-and-random-forests
#7
Trang T Le, W Kyle Simmons, Masaya Misaki, Jerzy Bodurka, Bill C White, Jonathan Savitz, Brett A McKinney
Motivation: Classification of individuals into disease or clinical categories from high-dimensional biological data with low prediction error is an important challenge of statistical learning in bioinformatics. Feature selection can improve classification accuracy but must be incorporated carefully into cross-validation to avoid overfitting. Recently, feature selection methods based on differential privacy, such as differentially private random forests and reusable holdout sets, have been proposed...
May 4, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28444127/hla-class-i-binding-prediction-via-convolutional-neural-networks
#8
Yeeleng S Vang, Xiaohui Xie
Motivation: Many biological processes are governed by protein-ligand interactions. One such example is the recognition of self and nonself cells by the immune system. This immune response process is regulated by the major histocompatibility complex (MHC) protein which is encoded by the human leukocyte antigen (HLA) complex. Understanding the binding potential between MHC and peptides can lead to the design of more potent, peptide-based vaccines and immunotherapies for infectious autoimmune diseases...
April 21, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28436837/passive-bci-in-operational-environments-insights-recent-advances-and-future-trends
#9
Pietro Arico, Gianluca Borghini, Gianluca Di Flumeri, Nicolina Sciaraffa, Alfredo Colosimo, Fabio Babiloni
OBJECTIVE: this mini-review aims to highlight recent important aspects to consider and evaluate when passive Brain-Computer Interface (pBCI) systems would be developed and used in operational environments, and remarks future directions of their applications. METHODS: Electroencephalography (EEG)-based pBCI has become an important tool for real-time analysis of brain activity, since it could potentially provide, covertly - without distracting the user from the main task - and objectively - not affected by the subjective judgement of an observer or the user itself - information about the operator cognitive state...
April 17, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28424657/magnetic-vestibular-stimulation-mvs-as-a-technique-for-understanding-the-normal-and-diseased-labyrinth
#10
REVIEW
Bryan K Ward, Jorge Otero-Millan, Prem Jareonsettasin, Michael C Schubert, Dale C Roberts, David S Zee
Humans often experience dizziness and vertigo around strong static magnetic fields such as those present in an MRI scanner. Recent evidence supports the idea that this effect is the result of inner ear vestibular stimulation and that the mechanism is a magnetohydrodynamic force (Lorentz force) that is generated by the interactions between normal ionic currents in the inner ear endolymph and the strong static magnetic field of MRI machines. While in the MRI, the Lorentz force displaces the cupula of the lateral and anterior semicircular canals, as if the head was rotating with a constant acceleration...
2017: Frontiers in Neurology
https://www.readbyqxmd.com/read/28423569/accurate-prediction-of-protein-protein-interactions-by-integrating-potential-evolutionary-information-embedded-in-pssm-profile-and-discriminative-vector-machine-classifier
#11
Zheng-Wei Li, Zhu-Hong You, Xing Chen, Li-Ping Li, De-Shuang Huang, Gui-Ying Yan, Ru Nie, Yu-An Huang
Identification of protein-protein interactions (PPIs) is of critical importance for deciphering the underlying mechanisms of almost all biological processes of cell and providing great insight into the study of human disease. Although much effort has been devoted to identifying PPIs from various organisms, existing high-throughput biological techniques are time-consuming, expensive, and have high false positive and negative results. Thus it is highly urgent to develop in silico methods to predict PPIs efficiently and accurately in this post genomic era...
April 4, 2017: Oncotarget
https://www.readbyqxmd.com/read/28420135/a-prosthetic-hand-body-area-controller-based-on-efficient-pattern-recognition-control-strategies
#12
Simone Benatti, Bojan Milosevic, Elisabetta Farella, Emanuele Gruppioni, Luca Benini
Poliarticulated prosthetic hands represent a powerful tool to restore functionality and improve quality of life for upper limb amputees. Such devices offer, on the same wearable node, sensing and actuation capabilities, which are not equally supported by natural interaction and control strategies. The control in state-of-the-art solutions is still performed mainly through complex encoding of gestures in bursts of contractions of the residual forearm muscles, resulting in a non-intuitive Human-Machine Interface (HMI)...
April 15, 2017: Sensors
https://www.readbyqxmd.com/read/28417600/a-bioinspired-mineral-hydrogel-as-a-self-healable-mechanically-adaptable-ionic-skin-for-highly-sensitive-pressure-sensing
#13
Zhouyue Lei, Quankang Wang, Shengtong Sun, Wencheng Zhu, Peiyi Wu
In the past two decades, artificial skin-like materials have received increasing research interests for their broad applications in artificial intelligence, wearable devices, and soft robotics. However, profound challenges remain in terms of imitating human skin because of its unique combination of mechanical and sensory properties. In this work, a bioinspired mineral hydrogel is developed to fabricate a novel type of mechanically adaptable ionic skin sensor. Due to its unique viscoelastic properties, the hydrogel-based capacitive sensor is compliant, self-healable, and can sense subtle pressure changes, such as a gentle finger touch, human motion, or even small water droplets...
April 18, 2017: Advanced Materials
https://www.readbyqxmd.com/read/28389030/harnessing-prefrontal-cognitive-signals-for-brain-machine-interfaces
#14
REVIEW
Byoung-Kyong Min, Ricardo Chavarriaga, José Del R Millán
Brain-machine interfaces (BMIs) enable humans to interact with devices by modulating their brain signals. Despite impressive technological advancements, several obstacles remain. The most commonly used BMI control signals are derived from the brain areas involved in primary sensory- or motor-related processing. However, these signals only reflect a limited range of human intentions. Therefore, additional sources of brain activity for controlling BMIs need to be explored. In particular, higher-order cognitive brain signals, specifically those encoding goal-directed intentions, are natural candidates for enlarging the repertoire of BMI control signals and making them more efficient and intuitive...
April 4, 2017: Trends in Biotechnology
https://www.readbyqxmd.com/read/28386448/elasticity-improves-handgrip-performance-and-user-experience-during-visuomotor-control
#15
Michael Mace, Paul Rinne, Jean-Luc Liardon, Catherine Uhomoibhi, Paul Bentley, Etienne Burdet
Passive rehabilitation devices, providing motivation and feedback, potentially offer an automated and low-cost therapy method, and can be used as simple human-machine interfaces. Here, we ask whether there is any advantage for a hand-training device to be elastic, as opposed to rigid, in terms of performance and preference. To address this question, we have developed a highly sensitive and portable digital handgrip, promoting independent and repetitive rehabilitation of grasp function based around a novel elastic force and position sensing structure...
February 2017: Royal Society Open Science
https://www.readbyqxmd.com/read/28376782/image-analysis-driven-single-cell-analytics-for-systems-microbiology
#16
Athanasios D Balomenos, Panagiotis Tsakanikas, Zafiro Aspridou, Anastasia P Tampakaki, Konstantinos P Koutsoumanis, Elias S Manolakos
BACKGROUND: Time-lapse microscopy is an essential tool for capturing and correlating bacterial morphology and gene expression dynamics at single-cell resolution. However state-of-the-art computational methods are limited in terms of the complexity of cell movies that they can analyze and lack of automation. The proposed Bacterial image analysis driven Single Cell Analytics (BaSCA) computational pipeline addresses these limitations thus enabling high throughput systems microbiology. RESULTS: BaSCA can segment and track multiple bacterial colonies and single-cells, as they grow and divide over time (cell segmentation and lineage tree construction) to give rise to dense communities with thousands of interacting cells in the field of view...
April 4, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28375650/emerging-frontiers-of-neuroengineering-a-network-science-of-brain-connectivity
#17
Danielle S Bassett, Ankit N Khambhati, Scott T Grafton
Neuroengineering is faced with unique challenges in repairing or replacing complex neural systems that are composed of many interacting parts. These interactions form intricate patterns over large spatiotemporal scales and produce emergent behaviors that are difficult to predict from individual elements. Network science provides a particularly appropriate framework in which to study and intervene in such systems by treating neural elements (cells, volumes) as nodes in a graph and neural interactions (synapses, white matter tracts) as edges in that graph...
March 27, 2017: Annual Review of Biomedical Engineering
https://www.readbyqxmd.com/read/28368026/network-based-characterization-and-prediction-of-human-dna-repair-genes-and-pathways
#18
Yan-Hui Li, Gai-Gai Zhang
Network biology is a useful strategy to understand cell's functional organization. In this study, for the first time, we successfully introduced network approaches to study properties of human DNA repair genes. Compared with non-DNA repair genes, we found distinguishing features for DNA repair genes: (i) they tend to have higher degrees; (ii) they tend to be located at global network center; (iii) they tend to interact directly with each other. Based on these features, we developed the first algorithm to predict new DNA repair genes...
April 3, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28336515/the-motor-activity-of-dna2-functions-as-an-ssdna-translocase-to-promote-dna-end-resection
#19
Maryna Levikova, Cosimo Pinto, Petr Cejka
DNA2 nuclease-helicase functions in DNA replication and recombination. This requires the nuclease of DNA2, while, in contrast, the role of the helicase activity has been unclear. We now show that the motor activity of both recombinant yeast and human DNA2 promotes efficient degradation of long stretches of ssDNA, particularly in the presence of the replication protein A. This degradation is further stimulated by a direct interaction with a cognate RecQ family helicase, which functions with DNA2 in DNA end resection to initiate homologous recombination...
March 1, 2017: Genes & Development
https://www.readbyqxmd.com/read/28323040/-machine-learning-based-identification-of-endogenous-cellular-microrna-sponges-against-viral-micrornas
#20
Soowon Kang, Seunghyun Park, Sungroh Yoon, Hyeyoung Min
A "miRNA sponge" is an artificial oligonucleotide-based miRNA inhibitor containing multiple binding sites for a specific miRNA. Each miRNA sponge can bind and sequester several miRNA copies, thereby decreasing the cellular levels of the target miRNA. In addition to developing artificial miRNA sponges, scientists have sought endogenous RNA transcripts and found that long non-coding RNAs, competing endogenous RNAs, pseudogenes, circular RNAs, and coding RNAs could act as miRNA sponges under precise conditions...
March 17, 2017: Methods: a Companion to Methods in Enzymology
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