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8th International Conference on Systems Biology, ISB 2014

作者： Hayashida, Morihiro Koyano, Hitoshi Akutsu, Tatsuya Bioinformatics Center Institute for Chemical Research Kyoto University Kyoto611-0011 Japan Department of Data Science Graduate School of Medicine Kyoto University Kyoto606-8507 Japan

ISBN: (纸本)9781479972944

Understanding of protein structures is important to find their functions. Many methods such as structural alignment, alignment-free similarity, and use of structural fragments have been developed for finding similar protein structures. In our previous study, we transformed protein structures into images each pixel of which represents the distance between the corresponding Cαatoms, and proposed similarity measures between two protein structures based on Kolmogorov complexity using image compression algorithms. In this paper, we examine efficient and effective image recognition techniques, SIFT (Scale Invariant Feature Transform) and SURF (Speeded Up Robust Features), which are invariant to image scaling, translation, and rotation, and partially invariant to affine or three-dimensional projection. We propose similarity based on SIFT and SURF, and apply it to classification of several protein structures. The results suggest that the similarity based on SURF outperforms several existing similarity measures including the compression-based similarity measures in our previous study, and that SIFT and SURF are useful for recognizing protein structures as well as objects in images. © 2014 IEEE.

关键词： Image recognition

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Sentiment Analysis: Indonesia Netflix User's Comment Using Multiple Lexicon-Based Dictionaries 4

Sentiment Analysis: Indonesia Netflix User's Comment Using M...

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4th International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Mola, Sebastianus Adi Santoso Widiastuti, Tiwuk Roma, Rosa V. K. Isabela Ohe Karnyoto, Andrea Stevens Pardamean, Bens University of Nusa Cendana Faculty of Science and Engineering Kupang Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331506490

A subscription movie streaming service from the United States, Netflix, has been present in Indonesia since 2016 and provides a wide variety of films without showing any single advertisements that can be viewed from anywhere, as long as there is access to the internet. Despite these advantages, many users have complained through the Google Play Store's comments column. Some of the common complaints include frequent buffering and connectivity issues, dissatisfaction with the limited selection of Indonesian movies, lack of subtitles for specific languages, or pricing concerns have also been raised. In this study developed two combined scenario methods using the InSet and SentiStrength-id dictionary to obtain better performance and compare them against independent InSet and SentiStrength-id. This study collected users' comments for the Netflix app in the Google Play Store as a dataset using web scraping techniques through the Google Collaboration tool. The dataset contains 3250 rows spanning the period from January 22, 2024, through June 6, 2024. To ensure proper processing of the text, data cleaning, lowercasing, normalization, tokenization, stemming, and stopwords removal are conducted. The results show that most user opinions are negative. The InSet dictionary has an accuracy of 92%, SentiStrength-id 78%, Combined scenario 1 is 87%, and scenario 2 reaches the highest among others which is 92.52%. © 2024 IEEE.

关键词： Video streaming

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Challenges in DNA sequence analysis on a production grid 2

Challenges in DNA sequence analysis on a production grid

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2012 EGI Community Forum / EMI 2nd Technical Conference, EGICF-EMITC 2012

作者： Van Schaik, Barbera D.C. Santcroos, Mark Korkhov, Vladimir Jongejan, Aldo Willemsen, Marcel Van Kampen, Antoine H.C. Olabarriaga, S lvia D. Bioinformatics Laboratory Department of Clinical Epidemiology Biostatistics and Bioinformatics Academic Medical Center Amsterdam Netherlands Faculty of Applied Math and Control Processes St. Petersburg State University Russia Biosystems Data Analysis Swammerdam Institute for Life Science University of Amsterdam Amsterdam Netherlands

Modern DNA sequencing machines produce data in the range of 1-100 GB per experiment and with ongoing technological developments this amount is rapidly increasing. The majority of experiments involve re-sequencing of human genomes and exomes to find genomic regions that are associated with disease. There are many sequence analysis tools freely available, e.g. for sequence alignment, quality control and variant detection, and frequently new tools are developed to address new biological questions. Since 2008 we use workflow technology to allow easy incorporation of such software in our data analysis pipelines, as well as to leverage grid infrastructures for the analysis of large datasets in parallel. The size of the datasets has grown from 1 GB to 70 GB in 3 years, therefore adjustments were needed to optimize these workflows. Procedures have been implemented for faster data transfer to and from grid resources, and for fault recovery at run time. A split-and-merge procedure for a frequently used sequence alignment tool, BWA, resulted in a three-fold reduction of the total time needed to complete an experiment and increased efficiency by a reduction in number of failures. The success rate was increased from 10% to 70%. In addition, steps to resubmit workflows for partly failed workflows were automated, which saved user intervention. Here we present our current procedure of analyzing data from DNA sequencing experiments, comment on the experiences and focus on the improvements needed to scale up the analysis of genomics data at our hospital. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike Licence.

关键词： data transfer

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bioinformatics Commons: The Cornerstone of Life and Health sciences

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Genomics,Proteomics & bioinformatics 2018年第4期16卷 223-225页

作者： Zhang Zhang Yu Xue Fangqing Zhao BIG Data Center and CAS Key Laboratory of Genome Sciences & Information Beijing Institute of Genomics Chinese Academy of Sciences Department of Bioinformatics & Systems Biology MOE Key Laboratory of Molecular Biophysics College of Life Science and Technology and the Collaborative Innovation Center for Biomedical Engineering Huazhong University of Science and Technology Beijing Institutes of Life Science Chinese Academy of Sciences

bioinformatics, an interdisciplinary field that combines biology, mathematics, computer science, medicine, and health science, to integrate, analyze, and interpret biological data, is now becoming increasingly data-intensive. To dig out the treasure from big data powered by high-throughput sequencing technologies, it is highly dependent on bioinformatics Commons that involves a variety of fundamental resources, includ-

关键词： bioinformatics Commons The Cornerstone of Life and Health sciences

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Standard Multi-Layer Perceptron on Positive - Unlabeled Glycosylation Site dataset 8

Standard Multi-Layer Perceptron on Positive - Unlabeled Glyc...

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8th International Conference on Computer science and Computational Intelligence, ICCSCI 2023

作者： Mahesworo, Bharuno Cenggoro, Tjeng Wawan Lumbanraja, Favorisen Rosyking Pardamean, Bens Statistics Department School of Computer Science Bina Nusantara University Indonesia Bioinformatics Data Science Research Center Bina Nusantara University Indonesia Computer Science Department School of Computer Science Bina Nusantara University Indonesia Computer Science Department School of Matematics and Natural Science University of Lampung Indonesia

The implementation of computational approaches for protein glycosylation site prediction is becoming popular since the experimental-validated glycosylation data became more abundant. Some of the data were found to be wrong after the experiment was again carried out with more sophisticated technology. To solve this issue, the latest state-of-the-art model trained the model based on a positive-unlabelled algorithm. The aim of this research is to explore the possibility of an approach applying a simple neural network algorithm and still achieve high classification performance. The model proposed in this research gave competitive results with fewer preprocessing steps. Increasing the accuracy of glycosylation site prediction can complement laboratory-based methods and is very useful for understanding the role of glycosylation. © 2023 The Authors. Published by Elsevier B.V.

关键词： Glycosylation PTM Site Prediction Standard Multi-Layer Perceptron

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Geospatial data and scholia 3

Geospatial data and scholia

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3rd International Workshop on Geospatial Linked data and the 2nd Workshop on Querying the Web of data, GeoLD-QuWeDa 2018

作者： Nielsen, Finn Årup Mietchen, Daniel Willighagen, Egon Cognitive Systems DTU Compute Technical University of Denmark Denmark Data Science Institute University of Virginia CharlottesvilleVA United States Dept of Bioinformatics - BiGCaT NUTRIM Maastricht University Netherlands

Scholia is a website that displays information about scientific works represented in Wikidata. It extracts the information via queries to the extended SPARQL endpoint Wikidata Query Service (WDQS). Scholia handles geospatial data that may be rendered on maps with the default map output format available in WDQS. We describe the use of geospatial data in Scholia, how we combine it with other data-e.g., on topics, events and affiliations-and present a set of user stories to illustrate its current capabilities and its potential in light of the ongoing expansion of Wikidata and its integration with research-related resources. © CEUR-WS. All rights reserved.

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Genome-wide association study of intraocular pressure in population-based cohorts in Japan: The ToMMo Eye Study

Ophthalmology Science

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Ophthalmology science 2025年

作者： Nobuo Fuse Hayato Anzawa Miyuki Sakurai Ikuko N. Motoike Satoshi Nagaie Tomohiro Nakamura Akiko Miyazawa Eiichi N. Kodama Masatsugu Orui Yohei Hamanaka Tomoko Kobayashi Akira Uruno Makiko Taira Ritsuko Shimizu Naoki Nakaya Mami Ishikuro Taku Obara Fuji Nagami Soichi Ogishima Fumiki Katsuoka Masayuki Yamamoto Tohoku Medical Megabank Organization Tohoku University Sendai Japan Department of System Bioinformatics Tohoku University Graduate School of Information Sciences Sendai Japan Department of Data Science Kyoto Women's University Kyoto Japan Tohoku University International Research Institute of Disaster Science Sendai Japan Tohoku University Graduate School of Medicine Sendai Japan Advanced Research Center for Innovations in Next-Generation Medicine Tohoku University Sendai Japan

Purpose This study was conducted to elucidate the distribution and determinants of ocular biometric parameters and to assess the association between intraocular pressure (IOP) and single-nucleotide polymorphisms (SNPs) in the Japanese population-based genome cohort studies. Design Cross-sectional analysis involving genome-wide association studies (GWASs). Participants In total, 22,150 participants aged >18 years from the population cohort (CommCohort) and 11,302 participants from the birth and three-generation cohort (BirThree Cohort) of the ToMMo Eye Study were examined. Methods Participant underwent interviews, ophthalmic and physiological examinations, laboratory tests, and microarray analyses. GWASs were conducted in the CommCohort (discovery stage) and the BirThree Cohort (replication stage), followed by a meta-analysis. Associations of SNPs and IOP were evaluated using a genome-wide significance threshold (5×10 -8 ). Main Outcome Measures Association of SNPs with IOP and distributions of IOP by sex and age. Results In the discovery stage, the mean IOP of the right and left eye was 13.95 and 14.02 mmHg, respectively. In the replication stage, the corresponding values were 14.32 and 14.27 mmHg. A significant age-related reduction in IOP was observed in both stages (P < 0.001). GWASs identified 573 and 2 genome-wide significant SNPs in the discovery and replication stages, respectively. Meta-analysis revealed 1,601 significant SNPs across 21 loci on 11 chromosomes. Of these loci, 17 were previously known to be associated with IOP and/or glaucoma, while four— SEPT8 (Chr5), ALDH2 (Chr12), COL6A2 (Chr21), and WNT7B (Chr22)—were newly identified. Conclusions This large-scale GWAS in a Japanese population identified 21 loci associated with IOP, including four novel loci. The findings highlight both genetic similarities and population-specific variations in SNPs influencing IOP and provide valuable insights to enhance eye health care, including glaucoma management. (27

关键词： population-based cohort study intraocular pressure genome-wide association study (GWAS) genome-wide association study GWAS intraocular pressure IOP single-nucleotide polymorphisms SNPs primary open-angle glaucoma POAG normal-tension glaucoma NTG axial length AL principal component analysis PCA

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Lightweight Pedestrian Detection through Guided Filtering and Deep Learning 10

Lightweight Pedestrian Detection through Guided Filtering an...

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10th IEEE Global Conference on Consumer Electronics, GCCE 2021

作者： Muchtar, Kahlil Saddami, Khairun Bintang, Akhyar Cenggoro, Tjeng Wawan Pardamean, Bens Lin, Chih-Yang Ernita, Tia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Bina Nusantara University School of Computer Science Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Yuan-Ze University Department of Electrical And Engineering Taoyuan Taiwan

ISBN: (纸本)9781665436762

In this paper, we propose a novel approach to locate and detect moving pedestrians in a video. Our proposed method first locates the region of interest (ROI) using a background subtraction algorithm based on guided filtering. This novel background subtraction algorithm allows our method to also filter unexpected noises at the same time, which could benefit the performance of our proposed method. Subsequently, the pedestrians are detected using YOLOv3 within the provided ROI. Our experiments showed that the proposed method has a competitive performance in the CDNET2014 dataset with a fast-processing time. © 2021 IEEE.

关键词： Convolutional neural networks

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Multiple analyses indicate the specific association of NR1I3,C6 and TNN with low hip BMD risk

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Journal of Genetics and Genomics 2017年第6期44卷 327-330页

作者： Ying-Ying Han Lan-Juan Zhao Yong Lin Hao He Qing Tian Wei Zhu Hui Shen Xiang-Ding Chen Hong-Wen Deng Center of System Biomedical Sciences University of Shanghai for Science and Technology Center for Bioinformatics and Genomics Department of Global Biostatistics and Data ScienceSchool of Public Health and Tropical MedicineTulane University Laboratory of Molecular and Statistical Genetics and the Key Laboratory of Protein Chemistry and Developmental Biology of the Ministry of Education College of Life SciencesHunan Normal University

Low hip bone mineral density(BMD)is an important index for osteoporosis and is associated with hip fracture,which leads to more cases of disability and mortality than all other kinds of fractures(Kanis et al.,2007).BMD’s heritability is more than 60%(Arden et al.,1996).A number of candidate loci for BMD have been previously identified by Genome Wide Association Studies(GWAS)(Xiong et al.,2009;Karasik et al.,2010;Zhang et al.,2013).Nevertheless,many significant signals based on GWAS are

关键词： BMD ERE is in Multiple analyses indicate the specific association of NR1I3,C6 and TNN with low hip BMD risk of GWAS BRCA NR with

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Embedding Model Design for Producing Book Recommendation 4

Embedding Model Design for Producing Book Recommendation

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4th International Conference on Information Management and Technology, ICIMTech 2019

作者： Rahutomo, Reza Perbangsa, Anzaludin Samsinga Soeparno, Haryono Pardamean, Bens Bioinformatics Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Information System Department Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781728133331

Internet services often recommend contents to users in order to maintain the interaction. Recommendation system plays a major role to formulate and produce a series of recommendation based on users' behavior. Surprisingly, user-generated scoring or known as ratings are the main raw materials to learn the pattern of favorable contents of each user. As a part of collaborative filtering strategy, rating is considerable to be included in formulating recommended contents. In this research, the basic formulation to recommend books is discovered. The recommendation system has been tested on one random-picked user behavior and successfully has generated five recommended books by analyzing prior activities. The embedding model produced the recommended books with 59% of accuracy. This research is done to provide an insightful experience for developing content recommendation system in Binus University's corporate learning system. © 2019 IEEE.

关键词： Recommender systems

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