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作者： Luo, Waylon Wolf Kent State University

学位级别：M.S., Master of Science/Master of Surgery

Drug epidemics have been a major problem in the United States for decades. As of August 2022, recreational marijuana can be legally purchased in 19 states in the U.S and medical marijuana is legal in 37 states. The forward legalization of marijuana in states is a factor of increasing social media content about marijuana use among young adults. Widespread promotion of alcohol, tobacco and substances in social media and other forms of entertainment change social norms. A number of research groups study drug abuse contents on social media such as Instagram, Reddit, YouTube, Facebook and Twitter. Some researchers study drug abuse in popular songs and popular music videos. Yet none have discussed drug abuse lyrics on social media. In this study, we carry out our novel detection of drug-related lyrics on Twitter through two different approaches, the smith-waterman algorithm and natural language processing algorithm. We analyzed over 1.3 billion publicly available tweets from 2016 and 2017 to identify substance use lyrics. We collected 101,117 tweets that are references to substance use lyrics. The local sequence alignment algorithm or the smith-waterman algorithm can identify drug abuse lyrics with accuracy up to 81% where a machine learning algorithm, Long Short Term Memory (LSTM), can identify with accuracy up to 48.9%.

关键词： Drug abuse lyrics Twitter Popular music smith-waterman algorithm

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Searching Biological Sequence Databases Using Distributed Adaptive Computing

Searching Biological Sequence Databases Using Distributed Ad...

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作者： Pappas, Nicholas Peter Virginia Tech | University

Genetic research projects currently can require enormous computing power to processes the vast quantities of data available. Further, DNA sequencing projects are generating data at an exponential rate greater than that of the development microprocessor technology; thus, new, faster methods and techniques of processing this data are needed. One common type of processing involves searching a sequence database for the most similar sequences. Here we present a distributed database search system that utilizes adaptive computing technologies. The search is performed using the smith-waterman algorithm, a common sequence comparison algorithm. To reduce the total search time, an initial search is performed using a version of the algorithm, implemented in adaptive computing hardware, which is designed to efficiently perform the initial search. A final search is performed using a complete version of the algorithm. This two-stage search, employing adaptive and distributed hardware, achieves a performance increase of several orders of magnitude over similar processor based systems.

关键词： bioinformatics smith-waterman algorithm adaptive computing configurable computing sequence comparison sequence alignment FPGA Thesis

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Dynamic Linear Model for the Identification of miRNAs in Next-Generation Sequencing Data

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BIOMETRICS 2011年第4期67卷 1206-1214页

作者： Johnson, W. Evan Welker, Noah C. Bass, Brenda L. Brigham Young Univ Provo UT 84602 USA Univ Utah Salt Lake City UT 84112 USA

Next-generation sequencing technologies are poised to revolutionize the field of biomedical research. The increased resolution of these data promise to provide a greater understanding of the molecular processes that control the morphology and behavior of a cell. However, the increased amounts of data require innovative statistical procedures that are powerful while still being computationally feasible. In this article, we present a method for identifying small RNA molecules, called miRNAs, which regulate genes by targeting their mRNAs for degradation or translational repression. In the first step of our modeling procedure, we apply an innovative dynamic linear model that identifies candidate miRNA genes in high-throughput sequencing data. The model is flexible and can accurately identify interesting biological features while accounting for both the read count, read spacing, and sequencing depth. Additionally, miRNA candidates are also processed using a modified smithwaterman sequence alignment that scores the regions for potential RNA hairpins, one of the defining features of miRNAs. We illustrate our method on simulated datasets as well as on a small RNA Caenorhabditis elegans dataset from the Illumina sequencing platform. These examples show that our method is highly sensitive for identifying known and novel miRNA genes.

关键词： Bayesian methods Dynamic linear model Markov chain Monte Carlo miRNA prediction smith-waterman algorithm Solexa Illumina sequencing

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A Novel Fault Early Warning Model Based on Fault Gene Table for Smart Distribution Grids

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ENERGIES 2017年第12期10卷

作者： Xiang, Min Min, Jie Wang, Zaiqian Gao, Pan Chongqing Univ Posts & Telecommun Key Lab Ind Internet Things & Networked Control Chongqing 400065 Peoples R China

Since a smart distribution grid has a diversity of components and complicated topology;it is very hard to achieve fault early warning for each part. A fault early warning model for smart distribution grid combining a back propagation (BP) neural network with a gene sequence alignment algorithm is proposed. Firstly;the operational state of smart distribution grid is divided into four states;and a BP neural network is adopted to explore the operational state from the historical fault data of the smart distribution grid. This obtains the relationship between each state transition time sequence and corresponding fault, and is used to construct the fault gene table. Then;a state transition time sequence is obtained online periodically, which is matched with each gene in fault gene table by an improved smith-waterman algorithm. If the maximum match score exceeds the given threshold, the relevant fault will be detected early. Finally, plenty of time domain simulation is performed on the proposed fault early warning model to IEEE-14 bus. The simulation results show that the proposed model can achieve efficient early fault warning of smart distribution grids.

关键词： fault gene table smart distribution grid fault early warning gene sequence alignment smith-waterman algorithm

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Characterization of implied scenarios as families of common behavior

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JOURNAL OF SYSTEMS AND SOFTWARE 2019年 158卷

作者： de Melo, Caio Batista Fernandes Cancado, Andre Luiz Rodrigues, Genaina Nunes Univ Brasilia Dept Comp Sci Brasilia DF Brazil Univ Calif Irvine Dept Comp Sci Irvine CA USA Univ Brasilia Dept Stat Brasilia DF Brazil

Concurrent systems face a threat to their reliability in emergent behaviors, which are not included in the specification but can happen during runtime. When concurrent systems are modeled in a scenario-based manner, it is possible to detect emergent behaviors as implied scenarios (ISs) which, analogously, are unexpected scenarios that can happen due to the concurrent nature of the system. Until now, the process of dealing with ISs can demand significant time and effort from the user, as they are detected and dealt with in a one by one basis. In this paper, a new methodology is proposed to deal with various ISs at a time, by finding Common Behaviors (CBs) among them. Additionally, we propose a novel way to group CBs into families utilizing a clustering technique using the smith-waterman algorithm as a similarity measure. Thus allowing the removal of multiple ISs with a single fix, decreasing the time and effort required to achieve higher system reliability. A total of 1798 ISs were collected across seven case studies, from which 14 families of CBs were defined. Consequently, only 14 constraints were needed to resolve all collected ISs, applying our approach. These results support the validity and effectiveness of our methodology. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Dependability Implied scenarios Concurrent systems smith-waterman algorithm Hierarchical clustering

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Optimal multi-threshold quantization scheme for bioinformatics inspired cooperative spectrum sensing in cognitive radio networks

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INTERNATIONAL JOURNAL OF ELECTRONICS 2018年第12期105卷 2082-2098页

作者： Shah, Hurmat Ali Koo, Insoo Univ Ulsan Sch Elect Elect & Comp Engn Ulsan 680749 South Korea

Hard decision combination provides bandwidth efficiency but the results produced areunreliablewhile soft decision combination has better results but at theexpenseof much consumption of bandwidth. An acceptable trade-off is achieved between the two in case of quantized decision combination. In this paper an optimalquantizationscheme is proposed in which the local sensing information isquantizedso the maximum detection probability is met while the false alarm probability remains under a certain constraint. The proposed optimal scheme works on the basis of energy detection and the localquantizationthresholds are found through iterative search. smith-watermanalgorithm (SWA) is used to compare the local sensing reports of the CR users and similarity indexes are found for the CR users. The local sensing decisions of the CR users below a certain calculated threshold are rejected and are not included in the final decision combination at theFC. For detailed analysis,SWA-based rules of decision combination with optimalquantizationthresholds are compared with a scheme that employsSWA-based rules of decision combination with heuristically selectedquantizationthresholds and a conventional majority combination scheme. Simulation results show that the proposed scheme performs better than the other two schemes.

关键词： Cooperative spectrum sensing bionformatics quantized hard decision optimal quantization scheme smith-waterman algorithm

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Music Retrieval and Recommendation Scheme Based on Varying Mood Sequences

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INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS 2010年第2期6卷 1-16页

作者： Jun, Sanghoon Rho, Seungmin Hwang, Eenjun Korea Univ Sch Elect Engn Multimedia Informat Lab Seoul South Korea

A typical music clip consists of one or more segments with different moods and such mood information could be a crucial clue for determining the similarity between music clips. One representative mood has been selected for music clip for retrieval, recommendation or classification purposes, which often gives unsatisfactory result. In this paper, the authors propose a new music retrieval and recommendation scheme based on the mood sequence of music clips. The authors first divide each music clip into segments through beat structure analysis, then, apply the k-medoids clustering algorithm for grouping all the segments into clusters with similar features. By assigning a unique mood symbol for each cluster, one can transform each music clip into a musical mood sequence. For music retrieval, the authors use the smith-waterman (SW) algorithm to measure the similarity between mood sequences. However, for music recommendation, user preferences are retrieved from a recent music playlist or user interaction through the interface, which generates a music recommendation list based on the mood sequence similarity. The authors demonstrate that the proposed scheme achieves excellent performance in terms of retrieval accuracy and user satisfaction in music recommendation.

关键词： Artificial Neural Network Mood Sequence Music Recommendation Music Retrieval smith-waterman algorithm

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Methodology and Application of Pattern Mining in Multiple Alarm Flood Sequences ∗

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IFAC-PapersOnLine 2015年第8期48卷 657-662页

作者： Shiqi Lai Tongwen Chen Department of Electrical and Computer Engineering University of Alberta Edmonton T6G 2V4 Canada

Alarm floods have always been serious hazards in industrial process monitoring since they overwhelm operators with large amount of alarm messages raised within a short period of time. In this paper, we propose an algorithm to find an optimal alignment of multiple alarm flood sequences so that based on this alignment an alarm sequence pattern can be easily found. The pattern could reveal the correlation between alarm messages in the alarm floods, which cannot be obtained by applying other alarm management techniques such as delay timers and dead-bands. The pattern could also help find the root cause, locate badly designed part in alarm systems, and predict incoming alarm floods. A dataset from an actual chemical plant has been used to test the effectiveness of the proposed algorithm.

关键词： Alarm flood analysis Time-stamped sequences Multiple sequence alignment smith-waterman algorithm Industrial alarm monitoring

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A fast algorithm for genome-wide analysis of proteins with repeated sequences

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PROTEINS-STRUCTURE FUNCTION AND GENETICS 1999年第4期35卷 440-446页

作者： Pellegrini, M Marcotte, EM Yeates, TO Univ Calif Los Angeles Inst Mol Biol Los Angeles CA 90095 USA Univ Calif Los Angeles DOE Lab Struct Biol & Mol Med Los Angeles CA USA

We present a fast algorithm to search for repeating fragments within protein sequences. The technique is based on an extension of the smith-waterman algorithm that allows the calculation of sub-optimal alignments of a sequence against itself. We are able to estimate the statistical significance of all sub-optimal alignment scores. We also rapidly determine the length of the repeating fragment and the number of times it is found in a sequence. The technique is applied to sequences in the Swissprot database, and to 16 complete genomes, We find that eukaryotic proteins contain more internal repeats than those of prokaryotic and archael organisms. The finding that 18% of yeast sequences and 28% of the known human sequences contain detectable repeats emphasizes the importance of internal duplication in protein evolution. Proteins 1999;35:440-446, (C) 1999 Wiley-Liss, Inc.

关键词： sub-optimal alignments Poisson statistics tandem repeats smith-waterman algorithm internal duplications

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GPU-Accelerated Protein Sequence Alignment

GPU-Accelerated Protein Sequence Alignment

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Laiq Hasan Marijn Kentie Zaid Al-Ars Computer Engineering Lab TU Delft

ISBN: (纸本)9781424441211

smith-waterman (S-W) algorithm is an optimal sequence alignment method and is widely used for genetic databases. This paper presents a Graphics Processing Units (GPUs) accelerated S-W implementation for protein sequence alignment. The paper proposes a new sequence database organization and several optimizations to reduce the number of memory accesses. The new implementation achieves a performance of 21.4 GCUPS, which is 1.13 times better than the state-of-the-art implementation on an NVIDIA GTX 275 graphics card.

关键词： Bioinformatics Protein Sequence Alignment Database Organization smith-waterman algorithm GPUs

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