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18th international conference on Intelligent computing (ICIC)

作者： Zhang, Yue Chen, Yuehui Chen, Baitong Cao, Yi Chen, Jiazi Cong, Hanhan Univ Jinan Sch Informat Sci & Engn Jinan Peoples R China Univ Jinan Sch Artificial Intelligence Inst & Informat Sci & Jinan Peoples R China Xuzhou First Peoples Hosp Xuzhou Peoples R China Univ Jinan Shandong Prov Key Lab Network Based Intelligent C Sch Informat Sci & Engn Jinan Peoples R China Kyushu Univ Grad Sch Bioresource & Bioenvironm Sci Lab Zool Fukuoka Fukuoka Japan Shandong Normal Univ Sch Informat Sci & Engn Jinan Peoples R China

ISBN: (纸本)9783031138294;9783031138287

the study of Protein-dna binding sites is one of the fundamental problems in genome biology research. It plays an important role in understanding gene expression and transcription, biological research, and drug development. In recent years, language representation models have had remarkable results in the field of Natural Language Processing (NLP) and have received extensive attention from researchers. Bidirectional Encoder Representations for Transformers (BERT) has been shown to have state-of-the-art results in other domains, using the concept of word embedding to capture the semantics of sentences. In the case of small datasets, previous models often cannot capture the upstream and downstream global information of dna sequences well, so it is reasonable to refer the BERT model to the training of dna sequences. Models pre-trained with large datasets and then fine-tuned with specific datasets have excellent results on different downstream tasks. In this study, firstly, we regard dna sequences as sentences and tokenize them using K-mer method, and later utilize BERT to matrix the fixed length of the tokenized sentences, perform feature extraction, and later perform classification operations. We compare this method with current state-of-the-art models, and the dnaBERT method has better performance with average improvement 0.013537, 0.010866, 0.029813, 0.052611, 0.122131 in ACC, F1-score, MCC, Precision, Recall, respectively. Overall, one of the advantages of BERT is that the pre-training strategy speeds up the convergence in the network in migration learning and improves the learning ability of the network. dnaBER model has advantageous generalization ability on other dna datasets and can be utilized on other sequence classification tasks.

关键词： Protein-dna binding sites Transcription factor Traditional machine learning Deep learning Transformers BERT

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Domain-Based Nucleic-Acid Minimum Free Energy: Algorithmic Hardness and Parameterized Bounds 30

Domain-Based Nucleic-Acid Minimum Free Energy: Algorithmic H...

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30th international conference on dna computing and molecular programming, dna 30 2024

作者： Demaine, Erik D. Gomez, Timothy Grizzell, Elise Hecher, Markus Lynch, Jayson Schweller, Robert Shalaby, Ahmed Woods, Damien Massachusetts Institute of Technology United States University of Texas Rio Grande Valley United States Hamilton Institute Department of Computer Science Maynooth University Ireland

ISBN: (纸本)9783959773447

molecular programmers and nanostructure engineers use domain-level design to abstract away messy dna/RNA sequence, chemical and geometric details. Such domain-level abstractions are enforced by sequence design principles and provide a key principle that allows scaling up of complex multistranded dna/RNA programs and structures. Determining the most favoured secondary structure, or Minimum Free Energy (MFE), of a set of strands, is typically studied at the sequence level but has seen limited domain-level work. We analyse the computational complexity of MFE for multistranded systems in a simple setting were we allow only 1 or 2 domains per strand. On the one hand, with 2-domain strands, we find that the MFE decision problem is NP-complete, even without pseudoknots, and requires exponential time algorithms assuming SAT does. On the other hand, in the simplest case of 1-domain strands there are efficient MFE algorithms for various binding modes. However, even in this single-domain case, MFE is P-hard for promiscuous binding, where one domain may bind to multiple as experimentally used by Nikitin [Nat Chem., 2023], which in turn implies that strands consisting of a single domain efficiently implement arbitrary Boolean circuits. © Erik D. Demaine, Timothy Gomez, Elise Grizzell, Markus Hecher, Jayson Lynch, Robert Schweller, Ahmed Shalaby, and Damien Woods

关键词： Domain-based dna designs efficient algorithms fixed-parameter tractable minimum free energy NC NP-hard P-hard

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Simulated Annealing and Genetic Algorithms based heuristics for computing the Non-Uniform Contiguous Translocation Distance 18

Simulated Annealing and Genetic Algorithms based heuristics ...

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18th international conference on Innovations in Intelligent Systems and Applications (INISTA)

作者： Constantin, Maria Univ Bucharest Fac Math & Comp Sci Bucharest Romania

ISBN: (纸本)9798350368130

In this paper we study a classic combinatorial problem inspired by genome evolution that aims finding the minimum number of genome rearrangements required to derive one organism from another, thereby calculating the genetic distance between two organisms. More precisely, as part of this study, we consider only the genome rearrangements done by translocation events. the translocation operation is formally defined as a prefix interchange between two chromosomes, represented as strings over the dna alphabet. the translocation operation is called uniform if the strings are swapping prefixes of equal length. Otherwise, it is called non-uniform. A translocation operation generates two new chromosomes. If these chromosomes are produced in a single copy, the translocation is named contiguous. the translocation distance between two genomes (sets of chromosomes or strings) is defined as the minimum number of translocation operations required to transition from one set to the other. We propose two heuristic algorithms to estimate the non-uniform contiguous translocation distance for a target set of size one. One algorithm is based on simulated annealing, and the other is based on genetic algorithms. We execute the proposed algorithms on both synthetic and real data, then compare the experimental results with those obtained using a greedy-inspired approximation algorithm.

关键词： translocation distance simulated annealing genetic algorithms approximation algorithm optimisation genome evolution bio-inspired computing

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Unifying Genetics and Imaging: MRI-Based Classification of MGMT Genetic Subtypes Using Visual Transformers 18

Unifying Genetics and Imaging: MRI-Based Classification of M...

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18th IEEE international conference on Emerging Technologies, ICET 2023

作者： Babar, Ibrar Tahir, Asjid Haider, Arslan Ur Rehman, Hafeez Alazab, Moutaz National University of Computer and Emerging Sciences Department of Computer Science Peshawar Pakistan Oryx Universal College Department of Computing and Data Science Doha Qatar

ISBN: (纸本)9798350328172

Brain cancer can take many forms, but glioblastoma (GBM) is one of the most aggressive. To treat it effectively, doctors need to know the genetic subtype of a specific part of the tumor called the O-6-methylguanine-dna-methyltransferase (MGMT) promoter. this information is critical for making treatment decisions and predicting outcomes. However, traditional methods for predicting MGMT status have significant limitations. One of the main reasons for this poor performance is that these methods fail to capture small variations in MRI signatures that are essential for accurately predicting MGMT promoter methylation status. In this work, we propose a two-part approach to predict the MGMT methylation status. First, we use autoencoders to extract features from the MRI images, capturing intricate spatial patterns and representations. then, we feed these encoded features into a visual transformer architecture to learn long-range dependencies and contextually significant relationships among image regions. this innovative fusion of autoencoders and visual transformers allows us to harness both local and global information present in the MRI data. We utilized a dataset consisting of 1010 3D MRI images from patients with GBM. Half of the patients had MGMT promoter methylation, while the other half did not. the model achieved impressive results, including an overall accuracy score of 0.904, recall score of 0.902, precision score of 0.914, F1 score of 0.906, and specificity score of 0.906. these metrics far surpass the accuracy of conventional imaging techniques. © 2023 IEEE.

关键词： Magnetic resonance imaging

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i6mA-word2vec: A Newly Model Which Used Distributed Features for Predicting dna N6-Methyladenine Sites in Genomes 18th

i6mA-word2vec: A Newly Model Which Used Distributed Features...

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18th international conference on Intelligent computing (ICIC)

作者： Fu, Wenzhen Zhong, Yixin Chen, Baitong Cao, Yi Chen, Jiazi Cong, Hanhan Univ Jinan Sch Informat Sci & Engn Jinan Peoples R China Univ Jinan Sch Artificial Intelligence Inst Jinan Peoples R China Univ Jinan Informat Sci & Engn Jinan Peoples R China Xuzhou First Peoples Hosp Xuzhou Jiangsu Peoples R China Univ Jinan Sch Informat Sci & Engn Shandong Prov Key Lab Network Based Intelligent C Jinan Peoples R China Kyushu Univ Grad Sch Bioresource & Bioenvironm Sci Lab Zool Fukuoka Fukuoka Japan Shandong Normal Univ Sch Informat Sci & Engn Jinan Peoples R China

ISBN: (纸本)9783031138294;9783031138287

dna N6 methyladenine (6mA) is a widely studied and widespread epigenetic modification, which plays a vital role in cell growth and development. 6mA is present in many biological cellular processes, such as the regulation of gene expression and the rule of cross dialogue between transposon and histone modification. therefore, in some biological research, the prediction of the 6mA site is very significant. Unfortunately, the existing biological experimental methods are expensive both in time and money. And they cannot meet the needs of existing research. So it is high time to develop a targeted and efficient computing model. Consequently, this paper proposes an intelligent and efficient calculation model i6mA-word2vec for the discrimination of 6mA sites. In our work, we use word2vec from the field of natural language processing to carry out distributed feature encoding. the word2vec model automatically represents the target class topic. then, the extracted feature space was sent into the convolutional neural network as prediction input. the experimental prediction results show that our computational model has better performance.

关键词： Methylation of dna N6-methyladenine word2vec Deep learning

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Research on the Application of dna Cryptography in Electronic Bidding System 14th

Research on the Application of DNA Cryptography in Electroni...

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14th international conference on Bio-inspired computing: theories and Applications, BIC-TA 2019

作者： Liu, Jianxia Jiao, Yangyang Wang, Yibo Li, Hongxuan Zhang, Xuncai Cui, Guangzhao School of Information Management Nanjing University Nanjing210000 China School of Economics and Management Wuhan University Wuhan430072 China School of Electrical and Information Engineering Zhengzhou University of Light Industry Zhengzhou450002 China

ISBN: (纸本)9789811534140

With the rapid development of bidding market, a new type of bidding method-electronic bidding method has been widely used in the bidding market. this new-type of method is a program that the bidding is completed by graphics and textures. Generally, the electronic bidding provides doubles bidders with the data information of the transaction through the Internet. In this study we propose an information encryption and digital signature method based on dna cryptography which is combined with HASH function, symmetric encryption and asymmetric encryption comprehensively for the purpose of the information resources’ integrality, usability, security and reliability in the electronic bidding system. the results of the study show that our new method provides double guarantee for the bidding system under the role of symmetric encryption and asymmetric encryption used dna cryptography, and dna molecular encryption has the characteristics of electronic immunity, concealment, independent of mathematical problems, massive parallelism, etc. It provides a double guarantee for the bidding system. the security analysis results show that the algorithm can effectively protect the security and integrity of the bidder and bidder’s data information. © 2020, Springer Nature Singapore Pte Ltd.

关键词： dna

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Femtosecnod Laser Ablated Fiber SERS-dna Probe and Applications in Deafness Gene Detection

Femtosecnod Laser Ablated Fiber SERS-DNA Probe and Applicati...

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international conference on Optical Communications and Networks (ICOCN)

作者： Youfu Geng Yiwen Xu Xiaoling Tan Lina Wang Xuejin Li College of Physics and Optoelectronic Engeering Shenzhen University Shenzhen China The Electronic Communication Department Shenzhen Institute of Information Technology Shenzhen China

In this paper, a fiber SERS-dna probe was fabricated with femtosecond laser ablation and laser-induced silver particle deposition, and a single dna strand with a stem-ring molecular beacon was modified onto the probe. Deafness gene was detected in the target solution by monitoring the SERS signal intensity of the molecular beacon. the experimental results showed that low dna concentration down to 10 -10 M could be successfully detected with such a fiber SERS-dna probe, which shows an alternative method for the detection of virulence gene.

关键词： dna Probes Optical fiber networks Fiber lasers Optical fiber sensors Laser ablation

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Stretch-and-positioning of single stranded dna as a template for molecular construction

Stretch-and-positioning of single stranded DNA as a template...

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IEEE international conference on Micro Electro Mechanical Systems

作者： T. Kobayashi M. Washizu University of Tokyo Japan

the high-specificity self-assembling nature of dna makes the molecule a candidate for the template for the molecular construction. In order to construct a functional device, the template must be positioned onto a predetermined site on a substrate to allow external connections, and the components must be properly aligned onto the template. A key factor is the high yield of binding. Such high yield requires that the bases of the template dna be exposed so that its counterpart can interact freely, and the template be stretched to avoid folding or coiling that hampers the interaction. For this purpose, we have developed a method, by which a single-stranded dna is stretched and immobilized bridging over an electrode pair, with the molecular ends anchored while the middle part is left free to interact with foreign molecules.

关键词： dna Probes Electrodes Marine animals Fluorescence Electrostatics Sequences Bridge circuits Mathematics Biological cells

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Inference of combinatorial Boolean rules of synergistic gene sets from cancer microarray datasets

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BIOINFORMATICS 2010年第12期26卷 1506-1512页

作者： Park, Inho Lee, Kwang H. Lee, Doheon Korea Adv Inst Sci & Technol Dept Bio & Brain Engn Taejon 305701 South Korea

Motivation: Gene set analysis has become an important tool for the functional interpretation of high-throughput gene expression datasets. Moreover, pattern analyses based on inferred gene set activities of individual samples have shown the ability to identify more robust disease signatures than individual gene-based pattern analyses. Although a number of approaches have been proposed for gene set-based pattern analysis, the combinatorial influence of deregulated gene sets on disease phenotype classification has not been studied sufficiently. Results: We propose a new approach for inferring combinatorial Boolean rules of gene sets for a better understanding of cancer transcriptome and cancer classification. To reduce the search space of the possible Boolean rules, we identify small groups of gene sets that synergistically contribute to the classification of samples into their corresponding phenotypic groups (such as normal and cancer). We then measure the significance of the candidate Boolean rules derived from each group of gene sets;the level of significance is based on the class entropy of the samples selected in accordance with the rules. By applying the present approach to publicly available prostate cancer datasets, we identified 72 significant Boolean rules. Finally, we discuss several identified Boolean rules, such as the rule of glutathione metabolism (down) and prostaglandin synthesis regulation (down), which are consistent with known prostate cancer biology.

关键词： GENES GENE expression CANCER genetics dna microarrays COMPUTERS in medicine MEDICAL genetics

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three dimensional molecular modeling studies in AIDS research using high performance computing facilities: a ternary complex of HV-1 RT

Three dimensional molecular modeling studies in AIDS researc...

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Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： N.S. Yadav S. Laxminarayan J.S. Yadav V.N. Pandey S. Singh M.J. Modak Dept. of Biochem. Acad. Comput. Center Piscataway NJ USA Biomedical Engineering Program New Jersey Institute of Technology and John von Neuman Computer Network Princeton USA Department of Biochemistry and Molecular Biology and Academic Computing Center University of Medicine and Dentistry of New Jersey Piscataway NJ USA

the authors present here a complete three-dimensional molecular model structure of the ternary complex (Enzyme-dna-dNTP) of human immunodeficiency virus-type 1 reverse transcriptase (HIV-1 RT) using high performance computer simulation and molecular modeling techniques. the Ca coordinates of the crystal structure of HIV-1 RT-dna binary complex as well as biochemical properties of a number of mutant enzymes were used as the basis to model build a prepolymerase ternary complex in which Mg/sup 2+/ ions are also accommodated. the side chains of amino acid residues interacting with the template and primer strands and those stabilizing the dNTP and Mg/sup 2+/ ions in the active site pocket are clearly elucidated in the model. the structural information provided by this model should be useful in understanding the polymerase reaction mechanisms and should permit structure based drug design against HIV-1 RT.

关键词： Acquired immune deficiency syndrome High performance computing Biochemistry Spine Biological system modeling Biology computing dna Computer networks Amino acids Polymers

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