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Cellular deconvolution of GTEx tissues powers discovery of disease and cell-type associated regulatory variants (vol 11, 955, 2020)

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NATURE COMMUNICATIONS 2020年第1期11卷 955页

作者： Donovan, Margaret K. R. D'Antonio-Chronowska, Agnieszka D'Antonio, Matteo Frazer, Kelly A. University of California San Diego Bioinformatics and Systems Biology Graduate Program La Jolla USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) University of California San Diego Department of Biomedical Informatics La Jolla USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) University of California San Diego Department of Pediatrics and Rady Children’s Hospital La Jolla USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) University of California San Diego Department of Pediatrics and Rady Children’s Hospital La Jolla USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) University of California San Diego Institute for Genomic Medicine La Jolla USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242)

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

关键词： Gene expression Genetic association study RNA sequencing

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Comparing the Efficacy and Safety of Treating Chronic Hepatitis B Infection during Pregnancy with Lamivudine,Telbivudine,and Tenofovir:A Meta-analysis

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Journal of Clinical and Translational Hepatology 2019年第3期7卷 197-212页

作者： Shahnaz Sali Mohammad Darvishi Mojtaba GhasemiAdl Meisam Akhlaghdoust Azin Mirzazadeh Somayeh Elikaei Behjati Hossein Sheikh-Zeinolabedini Shervin Shokouhi Soheil Tavakolpour Infectious Diseases and Tropical Medicine Research Center Shahid Beheshti University of Medical SciencesTehranIran Department of Aerospace and Subaquatic Medicine Infectious Diseases and Tropical Medicine Research Center(IDTMRC)AJA University of Medical SciencesTehranIran Pharmaceutical Sciences Research Center Tehran University of Medical SciencesTehranIran Pars Advanced and Minimally Invasive Medical Manners Research Center Pars HospitalIran University of Medical SciencesTehranIran Joint Bioinformatics Graduate Program University of Arkansas Little Rock and University of Arkansas for Medical SciencesLittle RockARUSA The Genetics Department at Islamic Azad University Science and Research BranchTehranIran Infectious Diseases and Tropical Medicine Research Center Shahid Beheshti University of Medical SciencesTehran 198396-3113Iran

Background and Aims:The perinatal transmission of hepatitis B virus(HBV)remains an important global health ***,a systematic review and meta-analysis were conducted to evaluate the evidence regarding the efficacy and maternal/fetal safety of treating pregnant women with lamivudine,telbivudine(LdT),and tenofovir(TDF).Methods:A PubMed and Scopus search resulted in 1,076 records,which were reduced to 36,containing 7,717 pregnant women with chronic HBV infection and 7467 infants meeting the inclusion *** latest search was in August ***:Treatment with LdT,but not lamivudine and TDF,could significantly reduce the hepatitis B virus surface antigen-positive rate(odds ratio(OR)=0.37)in infants;it also led to higher rates of hepatitis B e antigen loss(OR=12.14),hepatitis B e antigen seroconversion(OR=8.93),and alanine aminotransferase normalization in mothers(OR=1.49).Each of these treatments was able to significantly reduce HBV DNA positivity at birth(total OR=0.19)and mother-to-child-transmission of HBV(total OR=0.15),and to cause higher rates of HBV DNA suppression in mothers(total OR=25.53).However,nucleos(t)ide analogues might also be involved in creatine kinase elevation(total OR=7.48).In contrast,no significant association was found between nucleos(t)ide analogue therapy and preterm/premature births,congenital malformation,low birth weight,and abortion or fetal/infant *** results suggested LdT's high capability of preventing ***,TDF failed to show significant associations to a reduced risk of mother-to-child-transmission,probably due to the low number of patients ***:Although using either lamivudine,LdT,orTDF could lead to more favorable maternal/fetal outcomes,LdT seemed to show more potential in resolving certain infant-and maternal-related *** studies on the safety profile of such treatments are required.

关键词： Hepatitis B virus Antiviral therapy Tenofovir Telbivudine Lamivudine Nucleos(t)ide analogues Pregnancy

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Mobile Application Implementation as Agriculture 4.0 Strategy for Sugarcane Yield Prediction

Mobile Application Implementation as Agriculture 4.0 Strateg...

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HCI and UX Conference in Indonesia (CHIuXiD), International

作者： Hangger Gahara Mawandha Reza Rahutomo Teddy Suparyanto Bens Pardamean Faculty of Agricultural Technology Institut Pertanian Stiper Yogyakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350304084

ISBN: (纸本)9798350304091

Information engineering strategies play a significant and transformative role in shaping the landscape of digital agriculture. It drives innovation and efficiency in modern farming practices, with a specific focus on enhancing the value of agricultural commodities, such as sugarcane. The application of mobile technology plays a crucial part in achieving increased sugarcane productivity. Mobile applications, equipped with advanced developer features, offer rapid and user-friendly access to vital information. Traditional methods of estimating sugarcane production relied on manual data recording on paper, followed by data transfer to computer systems, typically managed by sugar factory junior plant officers. This conventional approach presents several inherent weaknesses, including time and effort intensiveness during data recording and entry. Additionally, the potential for errors in calculation and data input is a concern. The storage capacity for paper-based documents is finite, and farmers are often unable to autonomously assess their production potential. The objective of this research is to confront these obstacles by creating a sugarcane production application for Android. This application functions as an information engineering approach focused on forecasting sugarcane yields for plantation owners and their assistants. The development procedure adhered to the systematic waterfall method, following the principles of the Software Development Life Cycle (SDLC) model. Data collection was carried out through observations, while interviews with junior plant officers provided valuable insights into sugarcane estimation techniques. Analysis involved the synthesis of observational and interview data to inform the design of the application’s interface and algorithmic system. The resulting application significantly simplifies the process of estimating production potential for farmers, enabling them to access sugarcane productivity data during harvest. Consequently, sugar

关键词： Productivity Operating systems Estimation Production facilities Raw materials Mobile applications Recording

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A Diversity Inventory Monitoring System of Riparian Vegetation

A Diversity Inventory Monitoring System of Riparian Vegetati...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Dian Pratama Putra Nanda Satya Nugraha Teddy Suparyanto Alam Ahmad Hidayat Digdo Sudigyo Bens Pardamean Faculty of Agricultural Technology STIPER Agricultural Institute Yogyakarta Indonesia Faculty of Agricultural Technology Faculty of Forestry STIPER Agricultural Institute Yogyakarta Yogyakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665453967

To strengthen conservation efforts for preserving biodiversity in a conservation area, forest inventory is important to understand the natural succession process in the area and to establish a monitoring strategy. Further, tree inventory aims to monitor the output yielded in the area. More specifically, the tree inventory in the watershed area plays a key role to achieve Sustainable Development Goals (SDG), especially in riparian zones which are also vital parts of green zones in forests. However, the traditional inventory approach is time-consuming and laborious therefore the development of an expert system to assist in inventory monitoring is required. In this study, we develop a monitoring system via a mobile application to collect, analyze and visualize tree inventory data. The application includes algorithms required to compute tree biodiversity, distribution, and richness for the given input of the data of all tree species in a conservation area. For the model validation stage, we compare the traditional inventory approach with our proposed application-based approach to compute diversity inventory in two riparian locations: Klaten Conservation Park and Wonosobo Conservation Park. After the three-day data collection in the areas, we obtain that the accuracy of reading data of our proposed system can achieve more than 90% in comparison with the manual approach. This demonstrates that the system can assist forestry workers to perform more efficient tree inventories in different locations.

关键词： Vegetation Manuals Forestry Soil Mobile applications Biodiversity Expert systems

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Unsupervised News Topic Modelling with Doc2Vec and Spherical Clustering

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Procedia Computer Science 2021年 179卷 40-46页

作者： Arif Budiarto Reza Rahutomo Hendra Novyantara Putra Tjeng Wawan Cenggoro Muhamad Fitra Kacamarga Bens Pardamean Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Information System Department School of Information System Bina Nusantara University Jakarta Indonesia 11480 Eureka AI Singapore Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

In the digital and Internet era, companies are racing to profile their target users based on their online activities. One of the reliable sources is the news articles they read that can represent their interests. However, extracting latent information from the news articles is not an easy task for a human. In this paper, we introduced a practical model to automatically extract latent information from news articles with pre-determined topics. Our proposed model used unsupervised learning, thus alleviating the need for humans to label news items manually. Doc2vec was used to generate word vectors for each article. Afterward, a spectral clustering algorithm was applied to group the data based on the similarity. A supervised Long Short Term Memory (LSTM) model was built to compare the clustering performance. The best 1, best 3, and best 5 scores were used to evaluate our model. The result showed that our model could not outperformed LSTM model for the best 1 score. However, the best 5 score result indicated that our model was sufficiently robust to cluster the articles based on topic similarity. Additionally, the proposed unsupervised model was implemented in both an on-premise server, and a cloud server. Surprisingly, our proposed method could run faster in the cloud server despite its less number of CPU cores.

关键词： Topic Modelling Latent Information News Article Document Embedding Spherical Clustering

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Identifying the minimal sets of distance restraints for FRET-assisted protein structural modeling

arXiv

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arXiv 2024年

作者： Liu, Zhuoyi Grigas, Alex T. Sumner, Jacob Knab, Edward Davis, Caitlin M. O’Hern, Corey S. Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Integrated Graduate Program in Physical and Engineering Biology Yale University New HavenCT06520 United States Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Department of Chemistry Yale University New HavenCT06520 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States

Proteins naturally occur in crowded cellular environments and interact with other proteins, nucleic acids, and organelles. Since most previous experimental protein structure determination techniques require that proteins occur in idealized, non-physiological environments, the effects of realistic cellular environments on protein structure are largely unexplored. Recently, Förster resonance energy transfer (FRET) has been shown to be an effective experimental method for investigating protein structure in vivo. Inter-residue distances measured in vivo can be incorporated as restraints in molecular dynamics (MD) simulations to model protein structural dynamics in vivo. Since most FRET studies only obtain inter-residue separations for a small number of amino acid pairs, it is important to determine the minimum number of restraints in the MD simulations that are required to achieve a given root-mean-square deviation (RMSD) from the experimental structural ensemble. Further, what is the optimal method for selecting these inter-residue restraints? Here, we implement several methods for selecting the most important FRET pairs and determine the number of pairs Nr that are needed to induce conformational changes in proteins between two experimentally determined structures. We find that enforcing only a small fraction of restraints, Nr/N 0.08, where N is the number of amino acids, can induce the conformational changes. These results establish the efficacy of FRET-assisted MD simulations for atomic scale structural modeling of proteins in vivo. © 2024, CC BY.

关键词： Conformations

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Neuronetworks: Analysis of brain pathology in Mucopolysaccharidoses – A systems biology approach

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Neuroscience Informatics 2022年第1期2卷 100036-100036页

作者： Villalba Silva, Gerda Cristal Matte, Ursula Universidade Federal do Rio Grande do Sul UFRGS Porto Alegre Brazil Bioinformatics Core Hospital de Clínicas de Porto Alegre Porto Alegre Brazil Graduate Program in Genetics Molecular Biology Porto Alegre Brazil Department of Genetics UFRGS Porto Alegre Brazil

Mucopolysaccharidoses (MPS) are rare lysosomal storage diseases characterized by defects in the activity of lysosomal hydrolases that degrade glycosaminoglycan, with progressive multisystemic involvement. Neurological damage is present in several MPS types. The relationship between the accumulation of glycosaminoglycans and the neurological disorder presented in these diseases remains unknown. For this purpose, we analyzed distinct types of MPS using publicly available transcriptomic data with a systems biology approach to search for clues about the pathophysiological mechanisms involved in the brain pathology of MPS. The most relevant proteins in the networks and ontology terms related to neurological damage in MPS were identified and compared among diseases. We performed the clustering analysis for GSE111906 (MPSI), GSE95224 (MPSII), GSE23075 (MPSIIIB), GSE15758 (MPSIIIB), and GSE76283 (MPSVII). Regarding biomarker discovery analysis, the top 10 genes were ranked according to the maximal clique centrality. Different ontologies were present in the different types of MPS. Ontologies were also present in all the MPS types, like axon guidance, Calcium signaling, PI3K-Akt signaling pathway, and Wnt signaling pathway. We hypothesize that these pathways are deranged because glycosaminoglycans play an essential role in the extracellular matrix composition, helping to regulate several processes. Systems biology approaches may help to understand the mechanisms of neuropathology in the different types of Mucopolysaccharidoses. © 2021 The Author(s)

关键词： Gene expression Gene ontology Mucopolysaccharidoses Network analysis Neurological impairment

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Implementation of Face Patterns and Smile Recognition for Intelligent Class Attendance Systems

Implementation of Face Patterns and Smile Recognition for In...

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International Conference of Computer and Informatics Engineering (IC2IE)

作者： Miftakhurrokhmat Teddy Suparyanto Gregorius Natanael Elwirehardja Shofiyati Nur Karimah Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Department of Informatics Faculty of Computer Science Universitas Amikom Yogyakarta Yogyakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

Students “attendance in class is one important success parameter in face-to-face learning processes. Conventional attendance systems, such as paper-based attendance sheets or identity card systems, require a long time in the manual recapitulation process. Without additional verifications, even computer vision-based methods are prone to fraudulent practices by the students instead of gaining their excitement and attention in a class. To stimulate students” attention in a class, this work designs an intelligent class attendance system, in which facial pattern and smile recognition are implemented by using the latter as an additional task-based verification to reduce the risks of fake attendance. For the face recognition module, this pilot study used FaceNet as a feature extractor combined with SVM for classification, whereas the Haar cascade algorithm is used for recognizing smiles. This face recognition pipeline was implemented as a service installed on minicomputers or Internet of Things (IoT) devices in each classroom and connected to an IP camera. Every recorded attendance will be sent as a notification to a mobile application for students that requires their active participation to confirm it with a smiling self-photo. The proposed pipeline obtained 92.86% accuracy on the test data, and 66.67% accuracy when evaluated in a real-life simulation setting through the implemented system. The lower accuracy in the simulation indicated that further improvements are indispensable, especially since the model obtained 28.57% False Negative Rate. Future studies will need to acquire more data and experiment with more efficient methods of attendance verification.

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Traveling fronts in self-replicating persistent random walks with multiple internal states

arXiv

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arXiv 2020年

作者： Ishihara, Keisuke George, Ashish B. Cornelius, Ryan Korolev, Kirill S. Max Planck Institute for the Physics of Complex Systems Nöthnitzer Strasse 38 Dresden01187 Germany Max Planck Institute of Molecular Cell Biology and Genetics Pfotenhauer Strasse 108 Dresden01307 Germany Department of Physics Boston University BostonMA02215 United States Graduate Program in Bioinformatics Boston University BostonMA02215 United States

Self-activation coupled to a transport mechanism results in traveling waves that describe polymerization reactions, forest fires, tumor growth, and even the spread of epidemics. Diffusion is a simple and commonly used model of particle transport. Many physical and biological systems are, however, better described by persistent random walks that switch between multiple states of ballistic motion. So far, traveling fronts in persistent random walk models have only been analyzed in special, simplified cases. Here, we formulate the general model of reaction-transport processes in such systems and show how to compute the expansion velocity for arbitrary number of states. For the two-state model, we obtain a closed-form expression for the velocity and report how it is affected by different transport and replication parameters. We also show that nonzero death rates result in a discontinuous transition from quiescence to propagation. We compare our results to a recent observation of a discontinuous onset of propagation in mi-crotubule asters and comment on the universal nature of the underlying mechanism. Copyright © 2020, The Authors. All rights reserved.

关键词： Deforestation

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Characterizing the mechanical response of metallic glasses to uniaxial tension using a spring network model

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Physical Review Materials 2023年第7期7卷 073605-073605页

作者： Aya Nawano Weiwei Jin Jan Schroers Mark D. Shattuck Corey S. O'Hern Department of Mechanical Engineering and Materials Science Yale University New Haven Connecticut 06520 USA Benjamin Levich Institute and Physics Department The City College of New York New York New York 10031 USA Department of Physics Yale University New Haven Connecticut 06520 USA Department of Applied Physics Yale University New Haven Connecticut 06520 USA Graduate Program in Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA

A coarse-grained spring network model is proposed for the prediction of the mechanical response of metallic glasses as a function of the microstructure prior to loading. This model describes the mechanical response of metallic glasses using a network of parallel springs that can break and reform, mimicking atomic rearrangements during deformation. We compare predictions of the spring network model for stress versus strain to results from numerical simulations of athermal quasistatic, uniaxial tensile deformation of Cu50Zr50 metallic glasses using Lennard-Jones (LJ) and embedded atom method (EAM) atomic interactions. We show that both the LJ and EAM models possess qualitatively similar stress σ versus strain γ curves. By specifying five parameters [ultimate strength, strain at ultimate strength, slopes of σ(γ) at γ=0 and at large strain, and strain at fracture where σ=0], we demonstrate that the spring network model can accurately describe the form of the stress-strain curves during uniaxial tension for the computational studies of Cu50Zr50, as well as recent experimental studies of several Zr-based metallic glasses.

关键词： Alloys Amorphous materials Glasses Packing & jamming problems Molecular dynamics

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