IPSJ Transactions on Bioinformatics最新文献

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Erratum: A High-speed Measurement System for Treadmill Spherical Motion in Virtual Reality for Mice and a Robust Rotation Axis Estimation Algorithm Based on Spherical Geometry [IPSJ Transactions on Bioinformatics Vol.16 pp.1-12] 虚拟现实中跑步机球面运动的高速测量系统和基于球面几何的鲁棒旋转轴估计算法[j] .生物信息学学报,Vol.16 pp.1-12。
IPSJ Transactions on Bioinformatics Pub Date : 2023-01-01 DOI: 10.2197/ipsjtbio.16.28
Satoshi Zuguchi, K. Sakamoto, N. Katayama, H. Mushiake
{"title":"Erratum: A High-speed Measurement System for Treadmill Spherical Motion in Virtual Reality for Mice and a Robust Rotation Axis Estimation Algorithm Based on Spherical Geometry [IPSJ Transactions on Bioinformatics Vol.16 pp.1-12]","authors":"Satoshi Zuguchi, K. Sakamoto, N. Katayama, H. Mushiake","doi":"10.2197/ipsjtbio.16.28","DOIUrl":"https://doi.org/10.2197/ipsjtbio.16.28","url":null,"abstract":"","PeriodicalId":38959,"journal":{"name":"IPSJ Transactions on Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68501853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Metabolic Network Analysis by Time-series Causal Inference Using the Multi-dimensional Space of Prediction Errors 基于预测误差多维空间的时间序列因果推理代谢网络分析
IPSJ Transactions on Bioinformatics Pub Date : 2023-01-01 DOI: 10.2197/ipsjtbio.16.13
Takashi Ohyama, Y. Tohsato
{"title":"Metabolic Network Analysis by Time-series Causal Inference Using the Multi-dimensional Space of Prediction Errors","authors":"Takashi Ohyama, Y. Tohsato","doi":"10.2197/ipsjtbio.16.13","DOIUrl":"https://doi.org/10.2197/ipsjtbio.16.13","url":null,"abstract":"","PeriodicalId":38959,"journal":{"name":"IPSJ Transactions on Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68501541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
AtLASS: A Scheme for End-to-End Prediction of Splice Sites Using Attention-based Bi-LSTM atlas:一种使用基于注意力的Bi-LSTM的端到端剪接位点预测方案
IPSJ Transactions on Bioinformatics Pub Date : 2023-01-01 DOI: 10.2197/ipsjtbio.16.20
R. Harada, Keitaro Kume, Kazumasa Horie, T. Nakayama, Y. Inagaki, T. Amagasa
{"title":"AtLASS: A Scheme for End-to-End Prediction of Splice Sites Using Attention-based Bi-LSTM","authors":"R. Harada, Keitaro Kume, Kazumasa Horie, T. Nakayama, Y. Inagaki, T. Amagasa","doi":"10.2197/ipsjtbio.16.20","DOIUrl":"https://doi.org/10.2197/ipsjtbio.16.20","url":null,"abstract":"","PeriodicalId":38959,"journal":{"name":"IPSJ Transactions on Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68501749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A High-speed Measurement System for Treadmill Spherical Motion in Virtual Reality for Mice and a Robust Rotation Axis Estimation Algorithm Based on Spherical Geometry 虚拟现实小鼠跑步机球面运动高速测量系统及基于球面几何的鲁棒旋转轴估计算法
IPSJ Transactions on Bioinformatics Pub Date : 2023-01-01 DOI: 10.2197/ipsjtbio.16.1
Satoshi Zuguchi, K. Sakamoto, N. Katayama, H. Mushiake
{"title":"A High-speed Measurement System for Treadmill Spherical Motion in Virtual Reality for Mice and a Robust Rotation Axis Estimation Algorithm Based on Spherical Geometry","authors":"Satoshi Zuguchi, K. Sakamoto, N. Katayama, H. Mushiake","doi":"10.2197/ipsjtbio.16.1","DOIUrl":"https://doi.org/10.2197/ipsjtbio.16.1","url":null,"abstract":"","PeriodicalId":38959,"journal":{"name":"IPSJ Transactions on Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68501450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Defecation Prediction System Using Bowel Sound 利用肠道声音预测排便系统
IPSJ Transactions on Bioinformatics Pub Date : 2022-01-01 DOI: 10.2197/ipsjtbio.15.17
Soki Marumoto, Takatomi Kubo, M. Tada, K. Ikeda
{"title":"Defecation Prediction System Using Bowel Sound","authors":"Soki Marumoto, Takatomi Kubo, M. Tada, K. Ikeda","doi":"10.2197/ipsjtbio.15.17","DOIUrl":"https://doi.org/10.2197/ipsjtbio.15.17","url":null,"abstract":"","PeriodicalId":38959,"journal":{"name":"IPSJ Transactions on Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68501680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Probabilistic Approach to Evaluate the Likelihood of Artificial Genetic Modification and Its Application to SARS-CoV-2 Omicron Variant 评估人工基因改造可能性的概率方法及其在SARS-CoV-2组粒变异中的应用
IPSJ Transactions on Bioinformatics Pub Date : 2022-01-01 DOI: 10.2197/ipsjtbio.15.22
H. Kakeya, Y. Matsumoto
{"title":"A Probabilistic Approach to Evaluate the Likelihood of Artificial Genetic Modification and Its Application to SARS-CoV-2 Omicron Variant","authors":"H. Kakeya, Y. Matsumoto","doi":"10.2197/ipsjtbio.15.22","DOIUrl":"https://doi.org/10.2197/ipsjtbio.15.22","url":null,"abstract":"A method to find a probability that a given bias of mutations occur naturally is proposed to test whether a newly detected virus is a product of natural evolution or a product of non-natural process such as genetic manipulation. The probability is calculated based on the neutral theory of molecular evolution and binominal distribution of non-synonymous (N) and synonymous (S) mutations. Though most of the conventional analyses, including dN/dS analysis, assume that any kinds of point mutations from a nucleotide to another nucleotide occurs with the same probability, the proposed model takes into account the bias in mutations, where the equilibrium of mutations is considered to estimate the probability of each mutation. The proposed method is applied to evaluate whether the Omicron variant strain of SARS-CoV-2, whose spike protein includes 29 N mutations and only one S mutation, can emerge through natural evolution. The result of binomial test based on the proposed model shows that the bias of N/S mutations in the Omicron spike can occur with a probability of 2.0 × 10−3 or less. Even with the conventional model where the probabilities of any kinds of mutations are all equal, the strong N/S mutation bias in the Omicron spike can occur with a probability of 3.7 × 10−3, which means that the Omicron variant is highly likely a product of non-natural process including artifact. © 2022 Information Processing Society of Japan.","PeriodicalId":38959,"journal":{"name":"IPSJ Transactions on Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68501766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Novel Metagenomic Binning Framework Using NLP Techniques in Feature Extraction 一种基于自然语言处理技术的宏基因组分类框架
IPSJ Transactions on Bioinformatics Pub Date : 2022-01-01 DOI: 10.2197/ipsjtbio.15.1
Viet Toan Tran, Hoang D. Quach, Phuong V. D. Van, Van Hoai Tran
{"title":"A Novel Metagenomic Binning Framework Using NLP Techniques in Feature Extraction","authors":"Viet Toan Tran, Hoang D. Quach, Phuong V. D. Van, Van Hoai Tran","doi":"10.2197/ipsjtbio.15.1","DOIUrl":"https://doi.org/10.2197/ipsjtbio.15.1","url":null,"abstract":"Without traditional cultures, metagenomics studies the microorganisms sampled from the environment. In those studies, the binning step results serve as an input for the next step of metagenomic projects such as assembly and annotation. The main challenging issue of this process is due to the lack of explicit features of metagenomic reads, especially in the case of short-read datasets. There are two approaches, namely, supervised and unsupervised learning. Unfortunately, only about 1% of microorganisms in nature is annotated. That can cause problems for supervised approaches when an under-study dataset contains unknown species. It is well-known that the main challenging issue of this process is due to the lack of explicit features of metagenomic reads, especially in the case of short-read datasets. Previous studies usually assumed that reads in a taxonomic label have similar k-mer distributions. Our new method is to use Natural Language Processing (NLP) techniques in generating feature vectors. Additionally, the paper presents a comprehensive unsupervised framework in order to apply different embeddings categorized as notable NLP techniques in topic modeling and sentence embedding. The experimental results present our proposed approach’s comparative performance with other previous studies on simulated datasets, showing the feasibility of applying NLP for metagenomic binning. The program can be found at https://github.com/vandinhvyphuong/NLPBimeta.","PeriodicalId":38959,"journal":{"name":"IPSJ Transactions on Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68501555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Predicting PRDM9 Binding Sites by a Convolutional Neural Network and Verification Using Genetic Recombination Map 基于卷积神经网络的PRDM9结合位点预测及基因重组图谱验证
IPSJ Transactions on Bioinformatics Pub Date : 2022-01-01 DOI: 10.2197/ipsjtbio.15.9
Takahiro Nakamura, T. Endo, N. Osada
{"title":"Predicting PRDM9 Binding Sites by a Convolutional Neural Network and Verification Using Genetic Recombination Map","authors":"Takahiro Nakamura, T. Endo, N. Osada","doi":"10.2197/ipsjtbio.15.9","DOIUrl":"https://doi.org/10.2197/ipsjtbio.15.9","url":null,"abstract":": PR domain-containing 9 (PRDM9) is a zinc-finger protein that binds to specific DNA motifs and induces the crossing-over between chromosomes, resulting in a high recombination rate around binding sites. Currently, the binding sites of PRDM9 are predicted with methods based on motif matching and Position-specific Weight Matrix (PWM). Meanwhile, the Convolutional Neural Network (CNN) has shown superior performance in recent studies to identify protein-binding regions in general, and it is expected to perform well in PRDM9 binding site prediction. In this study, we compared the performance of PWM and CNN for predicting PRDM9 binding sites with not only test data but also the correlation between the prediction score for a fragment and the local recombination rate to evaluate the performance without overfitting e ff ects. Approximately 170,000 genomic DNA fragments of the human genome containing the Chromatin Immuno-Precipitation with high-throughput sequencing (ChIP-seq) peak of PRDM9 were used for constructing PWM and CNN. We found that CNN outperformed PWM in terms of area under the ROC curve and other metrics. Furthermore, the prediction scores of CNN correlated more strongly with the local recombination rate than PWM. We discuss that the superior performance of CNN would be in part due to the ability of CNN to capture the feature of surrounding sequences of actual PRDM9-binding sites.","PeriodicalId":38959,"journal":{"name":"IPSJ Transactions on Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68501831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Method for Evaluating Motor Synchronization and Short-term Motor Memory Based on Forearm Synchronization Process to Sinusoidal Motion Visual Stimulus 基于前臂对正弦运动视觉刺激同步过程的运动同步与短期运动记忆评价方法
IPSJ Transactions on Bioinformatics Pub Date : 2021-01-01 DOI: 10.2197/IPSJTBIO.14.22
K. Aoki, K. Niijima, T. Yoshioka
{"title":"Method for Evaluating Motor Synchronization and Short-term Motor Memory Based on Forearm Synchronization Process to Sinusoidal Motion Visual Stimulus","authors":"K. Aoki, K. Niijima, T. Yoshioka","doi":"10.2197/IPSJTBIO.14.22","DOIUrl":"https://doi.org/10.2197/IPSJTBIO.14.22","url":null,"abstract":"","PeriodicalId":38959,"journal":{"name":"IPSJ Transactions on Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68500983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Selective Inference for High-order Interaction Features Selected in a Stepwise Manner 逐步选择高阶交互特征的选择性推理
IPSJ Transactions on Bioinformatics Pub Date : 2021-01-01 DOI: 10.2197/IPSJTBIO.14.1
S. Suzumura, K. Nakagawa, Yuta Umezu, K. Tsuda, I. Takeuchi
{"title":"Selective Inference for High-order Interaction Features Selected in a Stepwise Manner","authors":"S. Suzumura, K. Nakagawa, Yuta Umezu, K. Tsuda, I. Takeuchi","doi":"10.2197/IPSJTBIO.14.1","DOIUrl":"https://doi.org/10.2197/IPSJTBIO.14.1","url":null,"abstract":"","PeriodicalId":38959,"journal":{"name":"IPSJ Transactions on Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68501123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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