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A Review on the Applications of Transformer-based language models for Nucleotide Sequence analysis

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arXiv 2024年

作者： Ghosh, Nimisha Santoni, Daniele Saha, Indrajit Felici, Giovanni Odisha Bhubaneswar India Institute for System Analysis and Computer Science "Antonio Ruberti" National Research Council of Italy Rome Italy Department of Computer Science and Engineering National Institute of Technical Teachers’ Training and Research West Bengal Kolkata India

In recent times, Transformer-based language models are making quite an impact in the field of natural language processing. As relevant parallels can be drawn between biological sequences and natural languages, the models used in NLP can be easily extended and adapted for various applications in bioinformatics. In this regard, this paper introduces the major developments of Transformer-based models in the recent past in the context of nucleotide sequences. We have reviewed and analysed a large number of application-based papers on this subject, giving evidence of the main characterizing features and to different approaches that may be adopted to customize such powerful computational machines. We have also provided a structured description of the functioning of Transformers, that may enable even first time users to grab the essence of such complex architectures. We believe this review will help the scientific community in understanding the various applications of Transformer-based language models to nucleotide sequences. This work will motivate the readers to build on these methodologies to tackle also various other problems in the field of bioinformatics. © 2024, CC BY.

关键词： Nucleotides

A Trajectory-Based Stochastic Approach to Symbolic Control

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A Trajectory-Based Stochastic Approach to Symbolic Control

IEEE Conference on Decision and Control

作者： Alessandro Tenaglia Corrado Possieri Daniele Carnevale Department of Civil Engineering and Computer Science Engineering University of Rome Tor Vergata Rome Italy National Research Council of Italy Institute for System Analysis and Computer Science “A. Ruberti” Rome Italy

This paper presents two innovative approaches to design symbolic controllers for dynamical systems. The first novelty involves a new trajectory-based strategy for defining the states of a symbolic model, which provides a more accurate representation of the system's dynamics than the traditional grid-based technique. The second novelty concerns using a Bounded-parameter Markov Decision Process rather than a Finite Transition system to model the behavior of a symbolic model. This procedure allows for handling the system's stochastic behavior and considers uncertainties. The effectiveness of the novel approaches presented is demonstrated through numerical results.

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Text Sentiment analysis using Different Types of Recurrent Neural Networks

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Text Sentiment Analysis using Different Types of Recurrent N...

Image Processing and Capsule Networks (ICIPCN), International Conference on

作者： Tetyana Filimonova Oleg Pursky Vitalina Babenko Andrey Nechepourenko Victoria Shvets Volodymyr Gamaliy department of computer science and information technology State university of trade and economics Kyiv Ukraine department of computer systems Kharkiv national automobile and highway university Kharkiv Ukraine department of digital economy and system analysis State university of trade and economics Kyiv Ukraine

ISBN: (数字)9798350367171

ISBN: (纸本)9798350367188

This work presents the results of research aimed at comparing and analyzing Recurrent Neural Networks (RNNs), specifically LSTM (Long Short-Term Memory) and GRU (Gated Recurrent Unit) models to identify the effectiveness of these models in the sentiment analysis of text messages. LSTM and GRU sentiment analysis models have been developed. For model training, a public dataset from the social media platform Twitter, consisting of text messages and corresponding sentiment labels is used. Obtained study results allow to conclude that compared to LSTM, the GRU model has proved to be more effective specifically in the task of text classification, which resulted in higher accuracy and lower losses during training.

关键词： Training Analytical models Sentiment analysis Adaptation models Recurrent neural networks Accuracy Social networking (online)

LAPLACE–BELTRAMI EQUATIONS AND NUMERICAL CONFORMAL MAPPINGS ON SURFACES

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arXiv 2024年

作者： Hakula, Harri Rasila, Antti Department of Mathematics and System Analysis Aalto University P.O. Box 11100 AaltoFI–00076 Finland Department of Mathematics with Computer Science Guangdong Technion Israel Institute of Technology Guangdong Shantou515063 China Department of Mathematics with Computer Science Technion-Israel Institute of Technology Haifa32000 Israel

The conjugate function method is an algorithm for numerical computation of conformal mappings for simply and multiply connected domains. In this paper, the conjugate function method is extended to cover conformal mappings between Riemannian surfaces. The main challenge addressed here is the connection between Laplace–Beltrami equations on surfaces and the computation of the conformal modulus of a quadrilateral. We consider mappings of simply, doubly, and multiply connected domains. The numerical computation is based on an hp-adaptive finite element method. The key advantage of our approach is that it allows highly accurate computations of mappings on surfaces, including domains of complex boundary geometry involving strong singularities and cusps. The efficacy of the proposed method is illustrated via an extensive set of numerical experiments including error *** Codes 30C85, 30F10, 31A15, 65E05, 65E10, 65N30 Copyright © 2024, The Authors. All rights reserved.

关键词： Conformal mapping

analysis of a Data Set to Determine the Dependence of Airline Passenger Satisfaction 7th

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Analysis of a Data Set to Determine the Dependence of Airlin...

7th Computational Methods in systems and Software, CoMeSySo 2023

作者： Tynchenko, V.S. Borodulin Kleshko, I.I. Nelyub, V.A. Rukosueva Artificial Intelligence Technology Scientific and Education Center Bauman Moscow State Technical University Moscow105005 Russia Peter the Great St. Petersburg Polytechnic University Saint Petersburg Russia Department of Information Economic System Institute of Engineering and Economics Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Department of Systems Analysis and Operations Research Institute of Informatics and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Information-Control Systems Department Institute of Computer Science and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Department of Technological Machines and Equipment of Oil and Gas Complex School of Petroleum and Natural Gas Engineering Siberian Federal University Krasnoyarsk660041 Russia

ISBN: (纸本)9783031535512

This paper presents an analysis of a data set to determine the factors influencing airline passenger satisfaction. The study examines various criteria such as gender, customer type, age, travel type, class, and range to assess their impact on passenger satisfaction. The dataset consists of 25 columns, including attributes like Wi-Fi availability, convenience of online booking, seat comfort, in-flight entertainment, baggage handling, and overall satisfaction. The sample is relatively balanced, with equal representation of men and women, predominantly repeat customers, and a majority flying for business purposes. Key findings include a strong correlation between departure and arrival delays, higher satisfaction among passengers in business class, and positive ratings for Wi-Fi service correlating with overall satisfaction. Correlation analysis reveals interdependencies between different attributes, such as the influence of cleanliness on seat comfort and food and beverage ratings. In addition, a neural network forecasting model is used to estimate the average ratings of passengers, although with low accuracy, which was later excluded. Finally, a decision tree algorithm is utilized to identify the most significant attributes affecting passenger satisfaction words. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Baggage handling

A Sensitivity analysis of Cellular Automata and Heterogeneous Topology Networks: Partially-Local Cellular Automata and Homogeneous Homogeneous Random Boolean Networks

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arXiv 2024年

作者： Glover, Tom Eivind Jahren, Ruben Martinuzzi, Francesco Lind, Pedro Gonçalves Nichele, Stefano Department of Computer Science OsloMet - Oslo Metropolitan University Oslo Norway Department of Computer Science and Communication Østfold University College Halden Norway Simula Research Laboratory Numerical Analysis and Scientific Computing Oslo0164 Norway Center for Scalable Data Analytics and Artificial Intelligence Leipzig University Leipzig Germany Institute for Earth System Science & Remote Sensing Leipzig University Leipzig Germany Remote Sensing Centre for Earth System Research Leipzig University Leipzig Germany

Elementary Cellular Automata (ECA) are a well-studied computational universe that is, despite its simple configurations, capable of impressive computational variety. Harvesting this computation in a useful way has historically shown itself to be difficult, but if combined with reservoir computing (RC), this becomes much more feasible. Furthermore, RC and ECA enable energy-efficient AI, making the combination a promising concept for Edge AI. In this work, we contrast ECA to substrates of Partially-Local CA (PLCA) and Homogeneous Homogeneous Random Boolean Networks (HHRBN). They are, in comparison, the topological heterogeneous counterparts of ECA. This represents a step from ECA towards more biological-plausible substrates. We analyse these substrates by testing on an RC benchmark (5-bit memory), using Temporal Derrida plots to estimate the sensitivity and assess the defect collapse rate. We find that, counterintuitively, disordered topology does not necessarily mean disordered computation. There are countering computational"forces" of topology imperfections leading to a higher collapse rate (order) and yet, if accounted for, an increased sensitivity to the initial condition. These observations together suggest a shrinking critical range. © 2024, CC BY.

关键词： Sensitivity analysis

Correlation analysis and Predictive Factors for Building a Mathematical Model 1

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7th Computational Methods in systems and Software, CoMeSySo 2023

作者： Nelyub, V.A. Tynchenko, V.S. Gantimurov, A.P. Degtyareva, K.V. Kukartseva, O.I. Artificial Intelligence Technology Scientific and Education Center Bauman Moscow State Technical University Moscow105005 Russia Peter the Great St. Petersburg Polytechnic University Saint Petersburg Russia Information-Control Systems Department Institute of Computer Science and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Department of Technological Machines and Equipment of Oil and Gas Complex School of Petroleum and Natural Gas Engineering Siberian Federal University Krasnoyarsk660041 Russia Department of Information Economic System Institute of Engineering and Economics Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Department of Systems Analysis and Operations Research Institute of Informatics and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia

ISBN: (数字)9783031535499

ISBN: (纸本)9783031535482

The study, published in the journal Nature Medicine, looked at data on 1,000 people from China who were tracked over an average period of six years. The participants were divided into two groups: those who lived in areas with high levels of air pollution and those who lived in areas with low levels of air pollution. The study analyzed data on patients with lung cancer, including their age, gender, exposure to air pollution, alcohol consumption, dust allergy, occupational hazards, genetic risk, chronic lung disease, balanced diet, obesity, smoking, passive smoking, chest pain, cough, hemoptysis, fatigue, weight loss, shortness of breath, wheezing, difficulty swallowing, nail thickening and snoring. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Air pollution

The Secondary Circuit Insulation online Monitoring system based on Distributed Current Sampling

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The Secondary Circuit Insulation online Monitoring System ba...

New Energy and Power Engineering (ICNEPE), International Conference on

作者： Hengchu Shi Xiaofan Chen Yinyin Li Hao You Shoudong Xu Yong Liang China Southern Power Grid Yunnan Electric Power Dispatching and Control Center Kunming China System Analysis Department Scientific Research Institute of Yunnan Power Grid Kunming China School of Computer Science and Technology Beijing Jiaotong University Beijing China

ISBN: (数字)9798331516086

ISBN: (纸本)9798331516093

The secondary system is very important for the reliable power supply and safe production of the power system. It includes secondary equipment and secondary circuits. The connection status of the secondary circuits will directly affect the correct operation of protection and automation devices. To solve these devices misoperation and refuse to operate problems caused by the multipoint grounding of PT and CT secondary circuits in substations, this paper proposes an online monitoring system for the insulation status of secondary circuits based on distributed zero sequence current sampling method. This system could greatly reduce the workload of maintenance on the secondary circuits, improves operation efficiency, and ensures the reliable operation of the secondary circuit in substations.

关键词： Insulation Substations Grounding Circuits Power system reliability Maintenance Circuit faults Integrated circuit reliability Protection Monitoring

Predicting Transcription Factor Binding Sites using Transformer based Capsule Network

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arXiv 2023年

作者： Ghosh, Nimisha Santoni, Daniele Saha, Indrajit Felici, Giovanni Odisha Bhubaneswar751030 India Institute for System Analysis and Computer Science "Antonio Ruberti" National Research Council of Italy Via dei Taurini Rome00185 Italy Department of Computer Science and Engineering National Institute of Technical Teachers' Training and Research West Bengal Kolkata700106 India

Motivation: Prediction of binding sites for transcription factors is important to understand how they regulate gene expression and how this regulation can be modulated for therapeutic purposes. Although in the past few years there are significant works addressing this issue, there is still space for improvement. In this regard, a transformer based capsule network viz. DNABERT-Cap is proposed in this work to predict transcription factor binding sites mining ChIPseq datasets. DNABERT-Cap is a bidirectional encoder pre-trained with large number of genomic DNA sequences, empowered with a capsule layer responsible for the final prediction. Results: The proposed model builds a predictor for transcription factor binding sites using the joint optimisation of features encompassing both bidirectional encoder and capsule layer, along with convolutional and bidirectional long-short term memory layers. To evaluate the efficiency of the proposed approach, we use a benchmark ChIP-seq datasets of five cell lines viz. A549, GM12878, Hep-G2, H1-hESC and Hela, available in the ENCODE repository. The results show that the average area under the receiver operating characteristic curve score exceeds 0.91 for all such five cell lines. DNABERT-Cap is also compared with existing state-of-the-art deep learning based predictors viz. DeepARC, DeepTF, CNN-Zeng and DeepBind, and is seen to outperform them. Availability and implementation: The datasets used in this work along with code are available at https://***/NimishaGhosh/DNABERT-Cap/tree/main. © 2023, CC BY.

关键词： DNA sequences