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4th International Conference on Cybernetics and Intelligent System, ICORIS 2022

作者： Azizatikarna, Kians Parung, Deby Erina Amirullah, Dian Hidayat, Alam Ahmad Cenggoro, Tjeng Wawan Budiarto, Arif Simon Pardamean, Bens Genetics Indonesia Jakarta12940 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665453950

As the cost of genetic testing becomes more affordable each year, direct-to-customer (DTC) genetic testing services witness rapid market growth. This has encouraged the development of an easy-to-use website application to optimize potential customers to obtain informed choice regarding the offered DTC genetic testing as well as purchasing information. We present a wireframing process as a part of the agile software development process to build a web portal prototype for an Indonesia-based genetic testing service called DNAku. The approach in building the prototype used in this case is a part of the Agile Software Development Method. In brief, the wireframing stage resulted in this work consists of three main important outcomes. The first one is the use case diagram as a blueprint of this web-based system. A site map is then proposed as an extended version of the use case diagram which visualizes the whole pages with the links. Finally, based on this site map a series of page mock-ups are designed using Hyper Text Marking Language (HTML) and Cascading Style Sheets (CSS). The result of the prototype can be used as the basis for the next development stage, which is the coding stage based on the collected feedback from users. Considering the continuous application development via the wireframing method by taking into account the cycle of feedbacks from involved parties, this approach can strengthen the infrastructure to sustain DTC genetic business model, which has a niche market in Indonesia. © 2022 IEEE.

关键词： Sales

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The effect of visual advanced driver assistance systems on a following human driver in a mixed-traffic condition

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Procedia Computer Science 2023年 216卷 221-229页

作者： Dedy Ariansyah Bens Pardamean Giandomenico Caruso Bioinformatics and Data Science Research Centre Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia Department of Mechanical Engineering Politecnico di Milano Milan 20156 Italy

Rapid development in vehicular technology has caused more automated vehicle control to increase on the roads. Studies showed that driving in mixed traffic with an autonomous vehicle (AV) had a negative impact on the time headway (THW) of conventional vehicles (CVs) (i.e., driven by humans). To address this issue, there is a need to equip CV with visual advanced driver assistance systems (ADASs) that helps the driver maintain safe headway when driving near AVs. This study examines the perception of drivers using visual ADAS and their associated risk while driving behind the AV at constant and varying speeds. The preliminary results showed that while visual ADAS could help drivers keep the safe THW, it could affect drivers’ ability to react to emergencies. This implies that visual modality alone might not be sufficient and therefore requires some other feedback or intelligent transport systems to help drivers maintain safe driving in a mixed-traffic condition.

关键词： sustainable transport management platooning car-following visual advanced driver assistance system virtual realtiy

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The phase separation of SGS3 regulates antiviral immunity and fertility in Arabidopsis

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Science China(Life Sciences) 2023年第8期66卷 1938-1941页

作者： Yujie Han Xiaolin Zhang Ran Du Xiaoyi Shan Daoxin Xie MOE Laboratory of Bioinformatics Tsinghua-Peking Center for Life SciencesSchool of Life SciencesTsinghua UniversityBeijing 100084China Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program School of Life SciencesTsinghua UniversityBeijing 100084China Shenzhen Branch of Guangdong Laboratory for Lingnan Modern Agriculture Genome Analysis Laboratory of the Ministry of AgricultureAgricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhen 518124China

Dear Editor,As a conserved mechanism among eukaryotic organisms,RNA silencing is vital for suppressing gene expression at the transcriptional or posttranscriptional level to regulate multiple biological *** interfering RNAs(si RNAs)generated by Dicer proteins integrate with Argonaute(AGO)to form an RNA-induced silencing complex(RISC),in which RNA/DNA could be degraded/methylated through a sequence-specific manner(Ding et al.,2004).

关键词： immunity separation

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Identification of microRNA in the protist Trichomonas vaginalis

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Genomics 2009年第5期93卷 487-493页

作者： Lin, Wei-Chen Li, Sung-Chou Lin, Wen-Chang Shin, Jyh-Wei Hu, Song-Nian Yu, Xiao-Min Huang, Ting-Yun Chen, Shih-Chieh Chen, Hua-Chien Chen, Shu-Jen Huang, Po-Jung Ruei-Chi Gan, Richie Chiu, Cheng-Hsun Tang, Petrus Molecular Regulation and Bioinformatics Laboratory Chang Gung University Taoyuan 333 Taiwan Division of Microbiology Graduate Institute of Biomedical Sciences Chang Gung University Taoyuan 333 Taiwan Institute of Biomedical Informatics National Yang-Ming University Taipei 112 Taiwan Taiwan International Graduate Program in Bioinformatics Academia Sinica Taipei 115 Taiwan Institute of Biomedical Sciences Academia Sinica Taipei 115 Taiwan Department of Parasitology National Cheng Kung University Tainan 701 Taiwan Key Laboratory of Genome Sciences and Information Beijing Institute of Genomics Chinese Academy of Sciences Beijing China Graduate University Chinese Academy of Sciences Beijing China Department of Life Sciences Chang Gung University Taoyuan 333 Taiwan Molecular Medicine Research Center Chang Gung University Taoyuan 333 Taiwan Bioinformatics Center Chang Gung University Tao-Yuan 333 Taiwan Chang Gung Molecular Infectious Diseases Research Center Chang Gung Memorial Hospital Taoyuan 333 Taiwan

MicroRNAs (miRNAs) are a class of small noncoding RNAs that have important regulatory roles in multicellular organisms. However, miRNA has never been identified experimentally in protist. Direct cloning of 438 expressed miRNA tags by microRNA serial analysis of gene expression from the parasitic protist Trichomonas vaginalis identified nine candidate miRNAs. bioinformatics analysis of the corresponding genomic region revealed that these miRNA candidates contain a classical stem-loop-stem structure of pre-microRNAs. Analysis of the 20 nt long mature tva-miR-001 showed that it is an intergenic miRNA located at the scaffold DS113596. Tva-miR-001 was differentially expressed in the trophozoite, pseudocyst and amoeboid stages. Based on the experimental results of the present study, we provided solid evidence that protist possesses a miRNA regulating network comparable with multicellular organisms for the first time. © 2009 Elsevier Inc. All rights reserved.

关键词： MicroRNA Protist Trichomonas vaginalis

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Exploring transposable element-based markers to identify allelic variations underlying agronomic traits in rice

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Plant Communications 2022年第3期3卷 59-71页

作者： Haidong Yan David C.Haak Song Li Linkai Huang Aureliano Bombarely School of Plant and Environmental Sciences Virginia TechBlacksburgVA 24061USA Graduate Program in Genetics Bioinformatics and Computational Biology(GBCB)Virginia TechBlacksburgVA 24061USA Department of Grassland Science Animal Science and Technology CollegeSichuan Agricultural UniversityChengdu 611130China Department of Bioscience Universita degli Studi di Milano(UNIMI)20133 MilanoItaly Instituto de Biologıa Molecular y Celular de Plantas(IBMCP) UPV-CSIC46022 ValenciaSpain

Transposable elements(TEs)are a major force in the production of new alleles during domestication;nevertheless,their use in association studies has been limited because of their *** have developed a TE genotyping pipeline(TEmarker)and applied it to whole-genome genome-wide association study(GWAS)data from 176 Oryza sativa *** accessions to identify genetic elements associated with specific agronomic *** markers recovered a large proportion(69%)of single-nucleotide polymorphism(SNP)-based GWAS peaks,and these TE peaks retained ca.25%of the *** use of TEs in GWASs may reduce false positives associated with linkage disequilibrium(LD)among SNP markers.A genome scan revealed positive selection on TEs associated with agronomic *** found several cases of insertion and deletion variants that potentially resulted from the direct action of TEs,including an allele of LOC_Os11g08410 associated with plant height and panicle length ***,these findings reveal the utility of TE markers for connecting genotype to phenotype and suggest a potential role for TEs in influencing phenotypic variations in rice that impact agronomic traits.

关键词： transposable element marker agronomic trait rice GWAS

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Experimental modeling of Alzheimer's disease: Translational lessons from cross-taxon analyses

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Alzheimer's & Dementia 2025年第5期21卷 e70273页

作者： Konstantin B. Yenkoyan Maria M. Kotova Kirill V. Apukhtin David S. Galstyan Tamara G. Amstislavskaya Tatyana Strekalova Murilo S. de Abreu Vergine A. Chavushyan Lee Wei Lim Longen Yang Denis D. Rosemberg Allan V. Kalueff Neuroscience Laboratory COBRAIN Center Yerevan State Medical University after M. Heratsi Yerevan Armenia Neuroscience Program Sirius University of Science and Technology Sochi Russia Institute of Translational Biomedicine St. Petersburg State University St. Petersburg Russia Institute of Experimental Medicine Almazov National Medical Research Centre Ministry of Healthcare of Russian Federation St. Petersburg Russia Scientific Research Institute of Neurosciences and Medicine Novosibirsk Russia Research Institute of General Pathology and Pathophysiology Moscow Russia Graduate Program in Health Sciences Federal University of Health Sciences of Porto Alegre Porto Alegre Brazil Department of Biosciences and Bioinformatics School of Science Xi'an Jiaotong-Liverpool University Suzhou China Suzhou Municipal Key Laboratory of Neurobiology and Cell Signaling School of Science Xi'an Jiaotong-Liverpool University Suzhou China Laboratory of Experimental Neuropsychobiology Department of Biochemistry and Molecular Biology Natural and Exact Sciences Center Federal University of Santa Maria Santa Maria Brazil Graduate Program in Biological Sciences: Toxicological Biochemistry Federal University of Santa Maria Santa Maria Brazil The International Zebrafish Neuroscience Research Consortium (ZNRC) Slidell Louisiana USA

Alzheimer's disease (AD) is a severely debilitating neurodegenerative disease with a rapidly increasing global prevalence, poorly understood causes, and no efficient treatments. Experimental models are valuable for studying AD pathogenesis, including amyloid beta and tau accumulation, synaptic dysfunction, and neuroinflammation. While no model fully reproduces the disease, we take an evolutionary biology approach to discuss available models across taxa, from mammals (rodents, primates) to zebrafish, Drosophila melanogaster , and Caenorhabditis elegans . Evaluating their strengths and limitations provides insight into disease mechanisms and may refine research strategies for improved diagnostics and therapeutic screening. Traditional models have significantly contributed to AD research, yet their translational limitations highlight the need for physiologically relevant alternatives. Integrating humanized rodent models, zebrafish, organoids, and induced pluripotent stem cell–based systems—along with advances in bioengineering and genetic editing—may offer a more comprehensive framework to bridge the gap between preclinical research and clinical application. Highlights Experimental models across rodents, primates, zebrafish, fruit flies, and worms provide key insights into Alzheimer's disease (AD). Cross-taxon comparisons assess strengths and weaknesses in AD models. Evolutionary biology approaches refine experimental strategies for AD research. Diverse animal models improve understanding of AD pathogenesis. Cross-species models enhance diagnostics and therapeutic strategy development.

关键词： Alzheimer's disease animal models cross-taxon analyses evolutionary psychiatry translation medicine

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bioinformatics exploration into potential mechanisms of Calamus draco for colorectal cancer treatment

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Procedia Computer Science 2024年 245卷 127-136页

作者： Christian Kenneth Rudi Nirwantono Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Biotechnology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

As one of the cancer types with the highest incidence rates, colorectal cancer (CRC) would benefit from treatments with fewer side effects and reduced treatment-resistant potential. One of the options is to harness the anti-CRC potential of natural products. Previous studies have shown that Calamus draco exudate, dragon's blood, has anticancer activity in liver cancer and acute myeloid leukemia, but its bioactivity has not been studied in CRC. Here we conduct a bioinformatics study based on network pharmacology to explore the anti-CRC potential and mechanism of C. draco -derived compounds. The bioinformatics pipeline is composed of compound and target collection, biological network evaluation, and enrichment analysis. We found that there are 43 bioactive compounds from C. draco targeting 91 CRC-related targets, of which most compounds target MEN1, PTGS2, and IDH1. Further analyses show that the targets of C. draco are involved in the cellular response to hypoxia. By inhibiting those targets, C. draco bioactive compounds can potentially hinder angiogenesis and increase treatment response efficacy.

关键词： bioinformatics network pharmacology Calamus draco colorectal cancer drug discovery

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Author Correction: Droplet Hi-C enables scalable, single-cell profiling of chromatin architecture in heterogeneous tissues

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Nature biotechnology 2025年 2025 May 12页

作者： Lei Chang Yang Xie Brett Taylor Zhaoning Wang Jiachen Sun Ethan J Armand Shreya Mishra Jie Xu Melodi Tastemel Audrey Lie Zane A Gibbs Hannah S Indralingam Tuyet M Tan Rafael Bejar Clark C Chen Frank B Furnari Ming Hu Bing Ren Department of Cellular and Molecular Medicine University of California San Diego La Jolla CA USA. Biomedical Sciences Graduate Program University of California San Diego La Jolla CA USA. Medical Scientist Training Program University of California San Diego La Jolla CA USA. Department of Quantitative Health Sciences Lerner Research Institute Cleveland Clinic Foundation Cleveland OH USA. Systems Biology and Bioinformatics PhD Program Case Western Reserve University School of Medicine Cleveland OH USA. Bioinformatics and Systems Biology Program University of California San Diego La Jolla CA USA. Moores Cancer Center UC San Diego La Jolla CA USA. Department of Neurosurgery University of Minnesota Minneapolis MN USA. Department of Medicine University of California San Diego School of Medicine La Jolla CA USA. Department of Cellular and Molecular Medicine University of California San Diego La Jolla CA USA. biren@health.ucsd.edu. Moores Cancer Center UC San Diego La Jolla CA USA. biren@health.ucsd.edu. Center for Epigenomics Institute for Genomic Medicine School of Medicine University of California San Diego La Jolla CA USA. biren@health.ucsd.edu.

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Multivariate Time-Series Deep Learning for Joint Prediction of Temperature and Relative Humidity in a Closed Space 8

Multivariate Time-Series Deep Learning for Joint Prediction ...

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

作者： Gunawan, Fergianto E. Budiman, Arief S. Pardamean, Bens Juana, Endang Romeli, Sugiarto Cenggoro, Tjeng W. Purwandari, Kartika Hidayat, Alam A. Redi, Anak A.N.P. Asrol, Muhammad Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia PT Impack Pratama Industri Jakarta14350 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

An accurate predictive model of temperature and humidity plays a vital role in many industrial processes that utilize a closed space such as in agriculture and building management. With the exceptional performance of deep learning on time-series data, developing a predictive temperature and humidity model with deep learning is propitious. In this study, we demonstrated that deep learning models with multivariate time-series data produce remarkable performance for temperature and relative humidity prediction in a closed space. In detail, all deep learning models that we developed in this study achieve almost perfect performance with an R value over 0.99. © 2023 The Authors. Published by Elsevier B.V.

关键词： closed space deep learning humity prediction indoor temperature prediction

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FragGeneScan-plus for scalable high-throughput short-read open reading frame prediction

FragGeneScan-plus for scalable high-throughput short-read op...

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IEEE Symposium on Computational Intelligence and bioinformatics and Computational Biology (CIBCB)

作者： Dongjae Kim Aria S. Hahn Shang-Ju Wu Niels W. Hanson Kishori M. Konwar Steven J. Hallam Department of Computer Science University of British Columbia Vancouver Canada Department of Microbiology University of British Columbia Vancouver Canada Graduate Program in Bioinformatics University of British Columbia Vancouver Canada

A fundamental step in the analysis of environmental sequence information is the prediction of potential genes or open reading frames (ORFs) encoding the metabolic potential of individual cells and entire microbial communities. FragGeneScan, a software designed to predict intact and incomplete ORFs on short sequencing reads combines codon usage bias, sequencing error models and start/stop codon patterns in a hidden Markov model to find the most likely path of hidden states from a given input sequence, provides a promising route for gene recovery in environmental datasets with incomplete assemblies. However, the current implementation of FragGeneScan does not scale efficiently with increasing input data size. Thus, FragGeneScan cannot be applied to contemporary environmental datasets that can exceed 100s of Gb. Here, we present FragGeneScan-Plus, an improved implementation of the FragGeneScan gene prediction model that leverages algorithmic thread synchronization and efficient in-memory data management to utilize multiple CPU cores without blocking I/O operations. FragGeneScan-Plus can process data approximately 5-times faster than FragGeneScan using a single core and approximately 50-times faster using eight hyper-threaded cores when benchmarked against simulated and real world environmental datasets.

关键词： Instruction sets Buffer storage Hidden Markov models Synchronization Predictive models Prediction algorithms Soil

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