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arXiv 2024年

作者： Merleau, Nono S.C. O’Malley, Miguel Roldán, Érika Mukherjee, Sayan Center for Scalable Data Analytics and Artificial Intelligence Department of Computer Science Universität Leipzig Germany Max Planck Institute for Mathematics in the Sciences Germany Duke University Departments of Statistical Science Mathematics Computer Science and Biostatistics & Bioinformatics United States

Higher-dimensional sliding puzzles are constructed on the vertices of a d-dimensional hypercube, where 2d−l vertices are distinctly coloured. Rings with the same colours are initially set randomly on the vertices of the hypercube. The goal of the puzzle is to move each of the 2d − l rings to pre-defined target vertices on the cube. In this setting, the k-rule constraint represents a generalisation of edge collision for the movement of colours between vertices, allowing movement only when a hypercube face of dimension k containing a ring is completely free of other rings. Starting from an initial configuration, what is the minimum number of moves needed to make ring colours match the vertex colours? An algorithm that provides us with such a number is called God’s algorithm. When such an algorithm exists, it does not have a polynomial time complexity, at least in the case of the 15-puzzle corresponding to k = 1 in the cubical puzzle. This paper presents a comprehensive computational study of different scenarios of the higher-dimensional puzzle. A benchmark of three computational techniques, an exact algorithm (the A* search) and two approximately optimal search techniques (an evolutionary algorithm (EA) and reinforcement learning (RL)) is presented in this work. The experiments show that all three methods can successfully solve the puzzle of dimension three for different face dimensions and across various difficulty levels. When the dimension increases, the A* search fails, and RL and EA methods can still provide a generally acceptable solution, i.e. a distribution of a number of moves with a median value of less than 30. Overall, the EA method consistently requires less computational time, while failing in most cases to minimise the number of moves for the puzzle dimensions d = 4 and d = 5. © 2024, CC BY.

关键词： Evolutionary algorithms

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Docking of Human Band 3 Anion Transporter Proteins with Their Plasmodium falciparum Interactors Based on Short Linear Motifs

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American Journal of Molecular Biology 2024年第4期14卷 187-200页

作者： Fatoumata Gniné Fofana Ayoub Ksouri Cheickna Cisse Oussema Souiai Alia Benkahla Hedmon Okella Mamadou Sangare Jeffrey G. Shaffer Seydou Doumbia Mamadou Wele African Center of Excellence in Bioinformatics University of Sciences Techniques and Technologies of Bamako (USTTB) Bamako Mali Laboratory of BioInformatics BioMathematics and BioStatistics (BIMS) Institut Pasteur de Tunis University of Tunis El Manar Tunis Tunisia School of Veterinary Medicine University of California Davis Tulare USA Department of Biostatistics and Data Science Tulane University School of Public Health and Tropical Medicine New Orleans USA University Clinical Research Centre (UCRC) USTTB Bamako Mali

Plasmodium (P.) falciparum is a pathogen that causes severe forms of malaria. Protein interactions have been shown to occur between P. falciparum and human erythrocytes in human blood. The Band 3 Anion Transporter (B3AT) protein is considered the main invasive pathway for the parasite in erythrocytes that causes clinical symptoms for malaria in humans. The interactions between P. falciparum parasites and erythrocytes along this receptor have previously been explored. Short linear motifs (SLIMs) are short linear mediator sequences that involve several biological processes, acting as mediators of protein interactions identifiable by computational tools such as SLiMFinder. For a given protein, the identification of SLIMs allows predicting its interactors. Using the SLIMs approach, protein-protein interaction network analyses between P. falciparum and its human host, were used to identify a tryptophan-rich protein, A5K5E5_PLAVS as an essential interactor of B3AT. To better understand the interaction mechanism, a guided protein-protein docking approach based on SLIM motifs was performed for human B3AT and A5K5E5_PLAVS. The highlights of this important interaction between P. falciparum and its human host have the potential to pave the way to identify new therapeutic candidates.

关键词： Malaria Protein-Protein Docking Protein-Protein Interaction Short Linear Motifs

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Utilizing Semi-supervised Method in Predicting BRCA1 Pathogenicity Variants

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Procedia Computer Science 2023年 227卷 36-45页

作者： Alam Ahmad Hidayat Joko Pebrianto Trinugroho Rudi Nirwantono Digdo Sudigyo Bens Pardamean Department of Mathematics School of Computer Science Bina Nusantara University Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia 11480

Quantifying the effect of mutations in the BRCA1 gene is useful for understanding their clinical consequences on breast cancer. Machine learning models can be applied to predict the landscape of protein variant effects that might not be always accessible by experiments. In this work, we propose a simple semi-supervised learning method using a Gaussian mixture model to predict ∼90% of the unlabeled missense variants of the BRCA1 gene collected from the ClinVar database. High-quality embeddings are used as a feature of the protein sequences, extracted using the latest pre-trained transformer-based language protein model. A statistical test show that the protein embeddings are effective and robust for predicting pathogenicity. Further, the lower representations of the features are then fed into the semi-supervised model. The prediction performance of the model only for the labeled testing data achieves an AUC score and an accuracy of 79.27% and 71.58%, respectively. Using our defined pathogenic probability score, we find that ∼94% of variants in our unlabeled dataset are well-separated into either benign or pathogenic classes according to that scoring. Our scores obtain a moderate Spearman rank correlation with the results of established unsupervised variant effect models. Finally, our approach can potentially be developed for more accurate and biologically reliable predictions of the variant effects.

关键词： embeddings mutation effect language model protein sequence semi-supervised learning

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

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

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Sebastianus Adi Santoso Mola Tiwuk Widiastuti Rosa V. K. Isabela Ohe Roma Andrea Stevens Karnyoto Bens Pardamean Faculty of Science and Engineering University of Nusa Cendana Kupang 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)9798331506490

ISBN: (纸本)9798331506506

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%.

关键词： Sentiment analysis Dictionaries Accuracy Films Collaboration Pricing Motion pictures Tokenization Cleaning Internet

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Identification of Meteorological Parameters Affecting Dengue Hemorrhagic Fever Incidences 4

Identification of Meteorological Parameters Affecting Dengue...

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4th International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2022

作者： Asadi, Faisal Trinugroho, Joko Pebrianto Hidayat, Alam Ahmad Rahutomo, Reza Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information System Department Jakarta11480 Indonesia Binus Graduate Program Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665473279

Tropical disease is one of the infectious diseases that affect Indonesia. Many people die because of tropical diseases, such as dengue hemorrhagic fever (DHF), chikungunya, leprosy, lymphatic, and filariasis. The Indonesian government's lack of public policy is the main problem in treating and preventing tropical diseases. The paper aims to describe the analysis results of the incidence of DHF in Jakarta, Indonesia. The analysis used the DHF incidences data from the Jakarta Health service surveillance office representative and combined it with the meteorological parameters data. The meteorological parameters were collected from the Bureau of Meteorological Climatology and Geophysics (BMKG). The statistical analysis of this research used Pearson's correlation. The results show that the meteorological parameters affecting DHF incidences are temperature, humidity, and wind speed. © 2022 IEEE.

关键词： Correlation methods

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Identifying Important Usernames in 'Biofarma' Conversation using Twitter Network Analysis 7

Identifying Important Usernames in 'Biofarma' Conversation u...

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7th International Conference on Information Management and Technology, ICIMTech 2022

作者： Rahutomo, Reza Jariyah, Ainun Trinugroho, Joko Pebrianto Pardamean, Bens School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia BINUS Graduate Program-Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

This study analyzed interactions between Twitter users in conversations regarding Indonesia's state-owned vaccine manufacturer 'Biofarma' in 2021. The primary objective of this study is to identify Key Opinion Leaders (KOL) due to the need of authentic and trustworthy persona in social media. A technique called network centrality was employed in this research alongside four centrality measurements, namely degree of centrality, eigenvector centrality, betweenness centrality, and closeness centrality. Focused on using a reply network interaction dataset, the research discovered several important usernames with different roles that enlivened the conversation and have a potential for social media marketing optimization. © 2022 IEEE.

关键词： Marketing

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POS0750 WHO PARTICIPATES IN AN ONLINE SYMPTOM CHECKER? CHARACTERISTICS, ATTRITION AND REPRESENTATIVENESS IN THE RHEUMATIC? STUDY

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Annals of the Rheumatic Diseases 2024年 83卷 1128-1129页

作者： F. Zegers L. Qin D. Selani G. Gomon T.D. Maarseveen H.K. Glas A. Van Tubergen Y. Goekoop-Ruiterman M.J.T. Reinders E.B. Van den Akker C. Baatenburg de Jong L. Klareskog B. Axnäs E. Steyerberg R. Bos S. Le Cessie R. Knevel Leiden University Medical Center Department of Biomedical Data Sciences Leiden Netherlands Leiden University Medical Center Department of Rheumatology Leiden Netherlands Delft University of Technology Department of Intelligent Systems Pattern Recognition and Bioinformatics Delft Netherlands Reumazorg Zuid West Neder；anmd Goes Netherlands Maastricht University Medical Center Department of Internal Medicine Division of Rheumatology Maastricht Netherlands Maastricht University Care and Public Health Research Institute (CAPHRI) Maastricht Netherlands Haga Hospital Department of Rheumatology Den Haag Netherlands Delft Technical University Delft Bioinformatics Lab Delft Netherlands Leiden University Medical Center Leiden Computational Biology Department of Biomedical Data Sciences Leiden Netherlands Delft University of Technology The Delft Bioinformatics Lab Pattern Recognition and Bioinformatics Delft Netherlands ReumaNederland Amsterdam Netherlands (Solna) Karolinska Institutet Division for Rheumatology Department of Medicine Stockholm Sweden Elsa Science Stockholm Sweden University Medical Center Rotterdam Department of Public Health Erasmus MC Rotterdam Netherlands Medical Center Leeuwarden Department of Rheumatology Leeuwarden Netherlands Nij Smellinghe Hospital Department of Rheumatology Drachten Netherlands Leiden University Medical Center Department of Clinical Epidemiology Leiden Netherlands Newcastle University Translational and Clinical Research Institute Rheumatology Newcastle upon Tyne United Kingdom

Background: Online symptom checkers (OSCs) could provide guidance in the diagnostic process. The number of OSCs are expanding yet often lack rigorous validation. Rheumatic? is an online questionnaire designed to provide a fast and reliable risk assessment of possible rheumatic diagnoses for individuals with musculoskeletal complaints (MSCs). We set out to validate this tool by following individuals with MSCs. A key question is representativity of the participants as attrition bias can complicate the construction of a precise prediction model. Objectives: This project aims to assess aspects of attrition and selection bias in Rheumatic? by comparing participants who did and did not respond to the first follow-up survey, by comparing participants versus patients from general practitioners (GP) and rheumatology clinics, and by exploring variations in characteristics across different recruitment policies. Methods: Rheumatic? includes a baseline questionnaire about current symptoms and past diagnoses. Participants were recruited online, at primary care or at rheumatology outpatient clinics. Four surveys followed after 0, 3, 6 and 12 months, about source of recruitment, medication, further diagnoses etc. We considered data of July 2021 to July 2023. We compared participants who solely answered the questionnaire to those who also answered the first follow up survey. Secondly, we compared characteristics of participants across different sources of recruitment (i.e. at primary or secondary care clinics or online (Instagram, Facebook, Google, the Dutch Arthritis Association)). For this, we calculated differences in percentages with confidence intervals and applied chi squared tests. We assessed representability of the cohort with the expected target population by comparing age, sex and BMI of the participants with information on new patients with MSC from the same period at primary care (GP), Rheumatology clinics in the South West of the Netherlands (RZWN), and the Rheumatolog

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A Design of Childhood Stunting Assessment Feature with Agile UX Approach 8

A Design of Childhood Stunting Assessment Feature with Agile...

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8th International HCI and UX Conference in Indonesia, CHIuXiD 2022

作者： Rahutomo, Reza Perbangsa, Anzaludin Samsinga Asadi, Faisal Nirwantono, Rudi Pardamean, Bens Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program-Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665476645

multidisciplinary collaboration between public health, system engineering, and UX is able to generate a solution in healthcare problem like stunting. The principle of Agile UX gathers requirements to generate an application design. Currently, various website and mobile applications are available to be utilized for stunting research. StuntingDB is one of many web-based applications that specialized in stunting data management. The application required several types of users to operate hierarchically. This research focused on Public Health Officers' workflow that require a solution to in the form of assessment module for stunting DBMS by using Agile UX principle. The method collaborates agile team and UX team to solve Public Health Officer's difficulty in changing stunting status at pre-saved child patient's profile. Collaboration of both agile team and UX team successfully proposed an application design that system design. © 2022 IEEE.

关键词： Websites

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BERT-based Topic Modeling Approach for Malaria Research Publication 4

BERT-based Topic Modeling Approach for Malaria Research Publ...

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4th International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2022

作者： Hidayat, Alam Ahmad Nirwantono, Rudi Budiarto, Arif Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665473279

Malaria is a communicable disease with half of the global population at risk due to its high morbidity and mortality rates. A massive number of studies are dedicated to malaria research, so it plays a key role in formulating the proper prevention strategy and effective malaria treatment. With the overwhelming number of updated publications in the field, an unsupervised text mining approach such as topic modeling may provide an alternative method for the malaria researcher to keep pace with new insights. In this work, we collect metadata of malaria publications from the PubMed database to perform BERT-based topic modeling to find well-defined topics regarding malaria research. The method is largely based on the popular BERTopic pipeline. We compare the performance of three different language models to generate document embeddings from the data. The dimension reduction and the density-based clustering algorithm are used to cluster the embeddings. The topic representation is computed based on the semantic similarity of the class TF-IDF representation. The substance of the resulting topics is then manually annotated based on the top words of each topic. We demonstrate that by merging initial topics into larger topics using hierarchical clustering and manual content-based examination, the evaluated coherence measure can be further improved, thus enhancing the topic's interpretability. Our modeling result is able to extract ten major topics recurring in the malaria research publication published from 2017-2022. The result provides preliminary insight to understand the dynamics and patterns of malaria research over the years © 2022 IEEE.

关键词： Diseases

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database Design for Pre-Eclampsia Case Administration 8

Database Design for Pre-Eclampsia Case Administration

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8th International Conference on Information Technology and Digital Applications, ICITDA 2023

作者： Asadi, Faisal Elwirehardja, Gregorius Natanael Trinugroho, Joko Pebrianto Rahutomo, Reza Pardamean, Bens School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information System Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350344691

The Ministry of Health of Indonesia has referred to pre-eclampsia as one of the most severe diseases affecting women. As an urgency, it is crucial to administrate pre-eclampsia cases for disease prevention as a long-term national healthcare strategy. Regarding health science, case data was significant in developing research and innovation. However, the main problem regarding pre-eclampsia case administration is data handling, recording, and management incompetence. Hence, this research proposed a conceptual design of a database for pre-eclampsia case administration. The proposed design covered conceptual, logical, and physical design. We elaborate the concept into three concepts of pre-eclampsia disease: pre-treatment, treatment, and post-treatment. This study proposed a solution to gain more data and study pre-eclampsia disease in Indonesia. © 2023 IEEE.

关键词： Medical informatics

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