检索结果-内蒙古大学图书馆

Public Good Diffusion Limits Microbial Mutualism

Physical Review Letters 2015年第16期114卷 168102-168102页

作者： Rajita Menon Kirill S. Korolev Department of Physics and Graduate Program in Bioinformatics Boston University Boston Massachusetts 02215 USA

Standard game theory cannot describe microbial interactions mediated by diffusible molecules. Nevertheless, we show that one can still model microbial dynamics using game theory with parameters renormalized by diffusion. Contrary to expectations, greater sharing of metabolites reduces the strength of cooperation and leads to species extinction via a nonequilibrium phase transition. We report analytic results for the critical diffusivity and the length scale of species intermixing. Species producing slower public good is favored by selection when fitness saturates with nutrient concentration.

关键词： GAME theory MICROBIAL diversity METABOLITES DIFFUSION -- Measurement MUTUALISM

来源：评论

学校读者我要写书评

暂无评论

Enhancing Interoperability of Digital Twin in the Maintenance phase of Lifecycle 6

Enhancing Interoperability of Digital Twin in the Maintenanc...

引用

6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022

作者： Ariansyah, Dedy Pardamean, Bens Bina Nusantara University Bioinformatics and Data Science Research Centre Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program Computer Science Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350399615

In today's digitalization era, asset management has evolved following the rapid adoption of information systems and digital technologies. In the maintenance phase of the asset, Digital Twin (DT) emerges as an effective approach to improve failure recognition and structural damage prediction through DT-driven Prognostic and Health Monitoring (PHM). As a result, DT allows asset manager to proactively plan maintenance strategy to improve the availability of the assets. However, to reduce asset downtime in a cost-effective and time efficient manner, DT for maintenance phase needs to be integrated with other software systems that manage the provision of maintenance service and spare part such as computerized maintenance management system (CMMS) or Enterprise Resource Planning (ERP). Nevertheless, many of the developed DT in PHM were not equipped with semantic data model and hence, lacks interoperability with other systems (e.g., other DT or non-DT system) and limits the effective use of the DT. To qualify as an effective DT, it needs a semantical-enabled interface to connect with data and models from various domain to enable DT-driven decision-making. This paper leverages a rule-based ontology reasoning model to enhance DT interoperability with other maintenance software systems. The results depicts that the developed model paves a way for an effective use of DT-driven system in asset maintenance management. © 2022 IEEE.

关键词： CMMS Digital Twin ERP Maintenance Ontology

来源：评论

学校读者我要写书评

暂无评论

Variational quantum neural network with optimized ansatz for predicting malignant ventricular arrhythmias 9th

Variational quantum neural network with optimized ansatz for...

引用

9th International Conference on Computer Science and Computational Intelligence, ICCSCI 2024

作者： Dominic, Nicholas Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

Preventive strategies should be the utmost priority when dealing with diverse patients suffering from malignant ventricular arrhythmia (MVA) that can lead to sudden cardiac death (SCD). Electrocardiogram (ECG) data is commonly used as a predictor for MVA predictive models. In this study, all ECG signals from MIT-BIH databases were fragmented into five-minute durations with a frequency sampling of 128 Hz. To solve the absence of hybrid optimizations in Machine Learning (ML) models, a novel Variational Quantum Neural Network (VQNN) was invented. Empowered by deep learning capabilities and optimized quantum circuits design, VQNN achieved remarkable performances designated by an accuracy of up to 95.1%, a perfect 100% recall, and a 95.2% score of the area under the Receiver Operating Characteristic curve (AUC ROC) with Conjugate Gradient as an optimizer and EfficientSU2 as a quantum ansatz. Despite the susceptibility to quantum noise, this research settles a new trajectory of utilizing quantum variational algorithms to predict and expand its applicability for MVA cases. © 2024 The Authors.

关键词： Quantum computers

来源：评论

学校读者我要写书评

暂无评论

Integrative biological systems modeling:challenges and opportunities

引用

中国高等学校学术文摘·计算机科学 2009年第1期3卷 92-100页

作者： Jialiang WU Eberhard VOIT Department of Mathematics Bioinformatics Program Georgia Institute of Technology Atlanta GA 30332 USA Integrative BioSystems Institute Georgia Institute of Technology Atlanta GA 30332 USA The Wallace H. Coulter Department of Biomedical Engineering Georgia Institute of Technology Atlanta GA 30332 USA

Most biological systems are by nature hybrids consist of interacting discrete and continuous components,which may even operate on different time scales. Therefore,' it is desirable to establish modeling frameworks that are capable of combining deterministic and stochastic, discrete and continuous, as well as multi-timescale features. In the context of molecular systems biology, an example for the need of such a combination is the investigation of integrated biological pathways that contain gene regulatory, metabolic and signaling components, which may operate on different time scales and involve on-off switches as well as stochastic effects. The implementation of integrated hybrid systems is not trivial because most software is limited to one or the other of the dichotomies above. In this study, we first review the motivation for hybrid modeling. Secondly, by using the example of a toggle switch model, we illustrate a recently developed modeling framework that is based on the combination of biochemical systems theory (BST) and hybrid functional Petri nets (HFPN). Finally, we discuss remaining challenges and future opportunities.

关键词： biochemical systems theory Petri net hybrid modeling hybrid functional Petri net toggle switch canonical modeling stochastic delay

来源：评论

学校读者我要写书评

暂无评论

In limbo: Physiological monitoring of emergency department boarders

引用

The American journal of emergency medicine 2025年 92卷 219-221页

作者： Eugene Y Kim Benjamin L Ranard Angela M Mills Soojin Park Department of Emergency Medicine Columbia University Vagelos College of Physicians and Surgeons New York NY USA Program for Hospital and Intensive Care Informatics Department of Neurology Columbia University Vagelos College of Physicians and Surgeons New York NY USA. Electronic address: eyk7@cumc.columbia.edu. Program for Hospital and Intensive Care Informatics Department of Neurology Columbia University Vagelos College of Physicians and Surgeons New York NY USA Division of Pulmonary Allergy and Critical Care Medicine Department of Medicine Columbia University Vagelos College of Physicians and Surgeons New York NY USA. Electronic address: blr2152@cumc.columbia.edu. Department of Emergency Medicine Columbia University Vagelos College of Physicians and Surgeons New York NY USA. Electronic address: amm2513@cumc.columbia.edu. Departments of Neurology and Bioinformatics Columbia University Vagelos College of Physicians and Surgeons New York NY USA. Electronic address: sp3291@cumc.columbia.edu.

来源：评论

学校读者我要写书评

暂无评论

Sequence to Sequence Deep Learning Architecture for Forecasting Temperature and Humidity inside Closed Space 10

Sequence to Sequence Deep Learning Architecture for Forecast...

引用

10th International Conference on Cyber and IT Service Management, CITSM 2022

作者： Setiawan, Karli Eka Elwirehardja, Gregorius Natanael Pardamean, Bens Bina Nusantara University Binus Graduate Program Computer Science Program Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia

ISBN: (数字)9781665460743

ISBN: (纸本)9781665460743

Solar Dryer Dome (SDD), an agricultural facility for drying and preserving agricultural products, needs a smart ability to predict the future indoor climate accurately, including indoor temperature and indoor humidity, in order to optimize electricity usage. To overcome these challenges, deep learning has been a widely adopted method. This research aims to forecast the future indoor climate using time series data by implementing a sequence-to-sequence (seq2seq) architecture, which is mostly used in Natural Language Processing (NLP) tasks. The two proposed seq2seq models, Long Short-Term Memory (LSTM) seq2seq and Gated Recurrent Unit (GRU) seq2seq, have proven to be superior to the adapted LSTM and GRU. The results show that the seq2seq GRU model outperforms the adapted GRU baseline model by an average difference of 0.03013 in MAE and the seq2seq LSTM model outperforms the adapted LSTM baseline model by an average difference of 0.00941 in MAE. To the best of our knowledge, this is the first implementation of seq2seq models for indoor climate forecasting on the Room Climate dataset. © 2022 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Discovering peptides and computational investigations of a multiepitope vaccine target Mycobacterium tuberculosis

引用

Synthetic and Systems Biotechnology 2024年第3期9卷 391-405页

作者： Truc Ly Nguyen Heebal Kim Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences Seoul National UniversitySeoul08826Republic of Korea Interdisciplinary Program in Bioinformatics Seoul National UniversitySeoul08826Republic of Korea eGnome Inc.Seoul05836Republic of Korea

Mycobacterium tuberculosis(MTB)is the causative agent of tuberculosis(TB),a prevalent airborne infectious *** the availability of the Bacille Calmette-Guerin vaccine,its global efficacy remains modest,and tuberculosis persists as a significant global public health *** this challenge and advancing towards the End MTB Strategy,we developed a multiepitope vaccine(MEV)based on immunoinformatics and compu-tational *** screening of MBT protein identified immune-dominant epitopes based on Major Histocompatibility Complex(MHC)allele binding,immunogenicity,antigenicity,allergenicity,toxicity,and cytokine *** epitopes were integrated into an MEV construct with adjuvant and linkers,forming a fully immunogenic vaccine *** analyses encompassed the evaluation of immunological and physicochemical properties,determination of tertiary structure,molecular docking with Toll-Like Receptors(TLR),molecular dynamics(MD)simulations for all atoms,and immune *** MEV comprises 534 amino acids,featuring 6 cytotoxic T lymphocyte,8 helper T lymphocyte,and 7 linear B lymphocyte epitopes,demonstrating high antigenicity and ***,molecular docking studies and triplicate MD simulations revealed enhanced interactions and stability of MEV with the TLR4 complex compared to *** addition,the immune simulation indicated the capacity to effectively induce elevated levels of an-tibodies and cytokines,emphasizing the vaccine’s robust immunogenic *** study presents a promising MEV against TB,exhibiting favorable immunological and physicochemical *** findings provide theoretical support for TB vaccine *** study aligns with the global initiative of the End MTB Strategy,emphasizing its potential impact on addressing persistent challenges in TB control.

关键词： Mycobacterium tuberculosis Tuberculosis Multiepitope vaccine Docking molecular Molecular dynamics simulation Immune simulation

来源：评论

学校读者我要写书评

暂无评论

Elastic restricted Boltzmann machines for cancer data analysis

引用

Frontiers of Electrical and Electronic Engineering in China 2017年第2期5卷 159-172页

作者： Sai Zhang Muxuan Liang Zhongjun Zhou Chen Zhang Ning Chen Ting Chen Jianyang Zeng Institute for Interdisciplinary Information Sciences Tsinghua University Beijing 100084 China Department of Statistics University of Wisconsin-Madison Madison WI 53706-1685 USA Bioinformatics Division TNLIST Department of Computer Science and Technology Tsinghua University Beijing 100084 China Program in Computational Biology and Bioinformatics Univesity of Southern California Los Angeles CA 90089 USA

Background： Restricted Boltzmann machines （RBMs） are endowed with the universal power of modeling （binary） joint distributions. Meanwhile, as a result of their confining network structure, training RBMs confronts less difficulties when dealing with approximation and inference issues. But little work has been developed to fully exploit the capacity of these models to analyze cancer data, e.g., cancer genomic, transcriptomic, proteomic and epigenomic data. On the other hand, in the cancer data analysis task, the number of features/predictors is usually much larger than the sample size, which is known as the ＇~ 〉〉 N＂ problem and is also ubiquitous in other bioinformatics and computational biology fields. The ＂p 〉〉 N＂ problem puts the bias-variance trade-off in a more crucial place when designing statistical learning methods. However, to date, few RBM models have been particularly designed to address this issue. Methods： We propose a novel RBMs model, called elastic restricted Boltzmann machines （eRBMs）, which incorporates the elastic regularization term into the likelihood function, to balance the model complexity and sensitivity. Facilitated by the classic contrastive divergence （CD） algorithm, we develop the elastic contrastive divergence （eCD） algorithm which can train eRBMs efficiently. Results： We obtain several theoretical results on the rationality and properties of our model. We further evaluate the power of our model based on a challenging task -- predicting dichotomized survival time using the molecular profiling of tumors. The test results show that the prediction performance of eRBMs is much superior to that of the state-of-the-art methods. Conclusions： The proposed eRBMs are capable of dealing with the ＂p 〉〉 N＂ problems and have superior modeling performance over traditional methods. Our novel model is a promising method for future cancer data analysis.

关键词： RBMs regularization cancer data analysis survival time prediction

来源：评论

学校读者我要写书评

暂无评论

HAsh-MaP-ERadicator: Filtering Non-Target Sequences from Next Generation Sequencing Reads

HAsh-MaP-ERadicator: Filtering Non-Target Sequences from Nex...

引用

IEEE International Conference on bioinformatics and Biomedicine

作者： Jonathon Brenner Catherine Putonti Department of Computer Science Bioinformatics Program Loyola University Chicago Departments of Biology and Computer Science Bioinformatics Program Loyola University Chicago

ISBN: (纸本)9781467368001

Contemporary DNA sequencing technologies are continuously increasing throughput at ever decreasing costs. Moreover, due to recent advances in sequencing technology new platforms are emerging. As such computational challenges persist. The average read length possible has taken a giant leap forward with the PacBio and Nanopore solutions. Regardless of the platform used, impurities within the DNA preparation of the sample - be it from unintentional contaminants or pervasive symbiots - remains an issue. We have developed a new tool, HAsh-MaP-ERadicator (HAMPER), for the detection and removal of non-target, contaminating DNA sequences. Integrating hash-based and mapping-based strategies, HAMPER is both memory and time efficient while maintaining a high level of sensitivity. Moreover, HAMPER was designed for flexibility: reads of any size can be efficiently examined and the user can set parameters specific for the analysis of reads produced by a particular sequencer. To evaluate our method, mock sequencing runs were generated including various contaminating species and with variable rates of mutation revealing a high level of sensitivity and specificity. Reads that are not of interest can quickly be removed using HAMPER thus improving downstream analyses.

关键词： Sequence contamination Sequence homology Hash-mapping Homologous Sequences Pollutant rise level Filtration Platform Throughput Analyses, Sequence sequencer Flexibility

来源：评论

学校读者我要写书评

暂无评论

Swarm intelligence optimization for feature selection of biomolecules 14

Swarm intelligence optimization for feature selection of bio...

引用

14th International Conference on Computer Engineering and Systems, ICCES 2019

作者： Alkady, Walaa Gad, Walaa Bahnasy, Khaled Program of Bioinformatics Faculty of Computer and Information Sciences Ain Shams University Department of Information System Cairo Egypt Dean of Obour Institutes Cairo Egypt

ISBN: (纸本)9781728152608

The biological activity of molecules is usually measured in assays to establish the level of inhibition of signal transduction or metabolic pathways. Drug discovery involves the use of Quantitative Structure Activity Relationship (QSAR) to identify chemical structures that could have good inhibitory effects on specific targets and have low toxicity. QSAR has very complicated 3D structure. Therefore, the flower-based optimization model (FBOM) for molecules is proposed to solve the curse of dimensionality problems. Four performance measures: accuracy, precision, sensitivity and specificity are used to evaluate the proposed model. Molecules activity is predicted using support vector machine (SVM), Naive Bayesian (NB), K-Nearest Neighbor (KNN), Decision Tree (DT) and Neural Network (NN) Classifiers. The results of the proposed model are promising. The proposed model reduces the number of features to 8 features out of 1666 features. Moreover, the average classification accuracy reaches to 95%. © 2019 IEEE.

关键词： Molecules

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：