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Machine Learning Techniques for Predicting Bacillus subtilis Promoters [chapter]

Meika I. Monteiro, Marcilio C. P. de Souto, Luiz M. G. Gonçalves, Lucymara F. Agnez-Lima
<span title="">2005</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
In this paper, we present an empirical comparison of machine learning techniques such as Naive Bayes, Decision Trees, Support Vector Machines and Neural Networks to the task of predicting Bacillus subtilis  ...  In order to do so, we first built a data set of promoter and nonpromoter sequences for this organism.  ...  Motivated by this, in this paper, we apply machine learning techniques for the analysis of Bacillus subtilis (B. subtilis) promoters.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11532323_9">doi:10.1007/11532323_9</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yrcsuskfxvd5desnq665cq4yym">fatcat:yrcsuskfxvd5desnq665cq4yym</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190221035712/http://pdfs.semanticscholar.org/2c92/5ca234bc6947ae08095ad537c32bc44f3c88.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2c/92/2c925ca234bc6947ae08095ad537c32bc44f3c88.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11532323_9"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Toward Algorithms for Automation of Postgenomic Data Analyses: Bacillus subtilis Promoter Prediction with Artificial Neural Network

Rafael Vieira Coelho, Gabriel Dall'Alba, Scheila de Avila e Silva, Sergio Echeverrigaray, Ana Paula Longaray Delamare
<span title="2019-10-01">2019</span> <i title="Mary Ann Liebert Inc"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zlgxgb5uazdqdfh5i5hk25cjge" style="color: black;">Omics</a> </i> &nbsp;
We report here an original neural network approach for recognition and prediction of Bacillus subtilis promoters.  ...  The artificial neural network used as input 767 B. subtilis promoter sequences, while also aiming at identifying the architecture, provides the most optimal prediction.  ...  Funding Information This work was supported by grants from the National Council for Scientific and Technological Development (CNPq). Funding was received by Capes Foundation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1089/omi.2019.0041">doi:10.1089/omi.2019.0041</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31573385">pmid:31573385</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nedonoihn5bqzkm5mawe63qnke">fatcat:nedonoihn5bqzkm5mawe63qnke</a> </span>
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A computational method for prediction of xylanase enzymes activity in strains of Bacillus subtilis based on pseudo amino acid composition features

Shohreh Ariaeenejad, Maryam Mousivand, Parinaz Moradi Dezfouli, Maryam Hashemi, Kaveh Kavousi, Ghasem Hosseini Salekdeh, Jinn-Moon Yang
<span title="2018-10-22">2018</span> <i title="Public Library of Science (PLoS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s3gm7274mfe6fcs7e3jterqlri" style="color: black;">PLoS ONE</a> </i> &nbsp;
OPEN ACCESS Citation: Ariaeenejad S, Mousivand M, Moradi Dezfouli P, Hashemi M, Kavousi K, Hosseini Salekdeh G (2018) A computational method for prediction of xylanase enzymes activity in strains of Bacillus  ...  subtilis based on pseudo amino acid composition features.  ...  Reza Ghaffari for his comprehensive support of the project and sharing his wisdom with us during the course of this research.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pone.0205796">doi:10.1371/journal.pone.0205796</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oqylghy5onhitipw7lgy6zlrei">fatcat:oqylghy5onhitipw7lgy6zlrei</a> </span>
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CapsProm: A Capsule Network For Promoter Prediction [article]

Lauro Moraes and Pedro Silva and Eduardo Luz and Gladston Moreira
<span title="2021-12-07">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Our model, the CapsProm, could assist in the transfer of learning between organisms and expand its applicability.  ...  However, a universal architecture that could generalize to several organisms has not yet been achieved, and thus, requiring researchers to seek new architectures and hyperparameters for each new organism  ...  We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan X Pascal GPU used for this research.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2112.03710v1">arXiv:2112.03710v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jvtnbpaukzdxrc6uez7xufspxq">fatcat:jvtnbpaukzdxrc6uez7xufspxq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211209012853/https://arxiv.org/pdf/2112.03710v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/14/ad/14ad204ad8dc3b2edf7d387a5c861bebf3aba429.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2112.03710v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

iProEP: a computational predictor for predicting promoter

Hong-Yan Lai, Zhao-Yue Zhang, Zhen-Dong Su, Wei Su, Hui Ding, Wei Chen, Hao Lin
<span title="2019-06-13">2019</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xffwf5iw3fghrkxtvjnqqph5jy" style="color: black;">Molecular Therapy: Nucleic Acids</a> </i> &nbsp;
(D. melanogaster), Caenorhabditis elegans (C. elegans), Bacillus subtilis (B. subtilis), and Escherichia coli (E. coli).  ...  Support vector machine (SVM) was used to distinguish between promoters and non-promoters.  ...  C2017209244), and the Science Strength Promotion Programme of UESTC.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.omtn.2019.05.028">doi:10.1016/j.omtn.2019.05.028</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31299595">pmid:31299595</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6616480/">pmcid:PMC6616480</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xvusvkgp3bfpnpu2ubzdtc5vta">fatcat:xvusvkgp3bfpnpu2ubzdtc5vta</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210525082921/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC6616480&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/73/2d/732ddd9e338d92fe58897c32dcbdc7084da162f7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.omtn.2019.05.028"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> elsevier.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616480" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Recognition of prokaryotic and eukaryotic promoters using convolutional deep learning neural networks

Ramzan Kh. Umarov, Victor V. Solovyev, Igor B. Rogozin
<span title="2017-02-03">2017</span> <i title="Public Library of Science (PLoS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s3gm7274mfe6fcs7e3jterqlri" style="color: black;">PLoS ONE</a> </i> &nbsp;
The Bacillus subtilis promoters identification CNN model achieves Sn = 0.91, Sp = 0.95, and CC = 0.86.  ...  For human promoters Sn/Sp/CC accuracy of prediction reached 0.95/0.98/0,90 on TATA and 0.90/0.98/0.89 for non-TATA promoter sequences, respectively.  ...  Escherichia coli σ70 promoter sequences were extracted from manually curated RegulonDB [29] . Bacillus subtilis promoters were taken from a collection described in [30] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pone.0171410">doi:10.1371/journal.pone.0171410</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/28158264">pmid:28158264</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5291440/">pmcid:PMC5291440</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jilzdaugu5ekjefk6zlrke4qvu">fatcat:jilzdaugu5ekjefk6zlrke4qvu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20171012075024/http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0171410&amp;type=printable" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3f/7f/3f7ff48661979438d99c94aa8c3090ee1855f41d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pone.0171410"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> plos.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5291440" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Recognition of prokaryotic promoters based on a novel variable-window Z-curve method

Kai Song
<span title="2011-09-27">2011</span> <i title="Oxford University Press (OUP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hfp6p6inqbdexbsu4r7usndpte" style="color: black;">Nucleic Acids Research</a> </i> &nbsp;
To verify the prediction performance, the proposed method is applied to predict promoter fragments of two representative prokaryotic model organisms (Escherichia coli and Bacillus subtilis).  ...  The features are used for further classification by the partial least squares technique.  ...  Chun-Ting Zhang, the Department of Physics, Tianjin University, China, for instructing the methodology of Z-curve method. Conflict of interest statement. None declared.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1093/nar/gkr795">doi:10.1093/nar/gkr795</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/21954440">pmid:21954440</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC3273801/">pmcid:PMC3273801</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/f5nirpqynvhflgp5wtkfqvjjcq">fatcat:f5nirpqynvhflgp5wtkfqvjjcq</a> </span>
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Whole genome assembly of a natto production strain Bacillus subtilis natto from very short read data

Yukari Nishito, Yasunori Osana, Tsuyoshi Hachiya, Kris Popendorf, Atsushi Toyoda, Asao Fujiyama, Mitsuhiro Itaya, Yasubumi Sakakibara
<span title="">2010</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4srzxifvfrdlhjhg3dimznkp7m" style="color: black;">BMC Genomics</a> </i> &nbsp;
Bacillus subtilis natto is closely related to the laboratory standard strain B. subtilis Marburg 168, and functions as a starter for the production of the traditional Japanese food "natto" made from soybeans  ...  Completion of the assembly through long PCR experiments resulted in one connected scaffold for B. subtilis natto.  ...  Sato for technical assistance and Dr. K. Tsuge for discussion.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/1471-2164-11-243">doi:10.1186/1471-2164-11-243</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/20398357">pmid:20398357</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC2867830/">pmcid:PMC2867830</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vudmtbssnvcmzhnhvl6n4lspgm">fatcat:vudmtbssnvcmzhnhvl6n4lspgm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170830122927/https://bmcgenomics.biomedcentral.com/track/pdf/10.1186/1471-2164-11-243?site=http://bmcgenomics.biomedcentral.com" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/6a/6b/6a6b48303c1ce4865b9e284a1b017310d6422846.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/1471-2164-11-243"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2867830" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

The relative value of operon predictions

R. W. W. Brouwer, O. P. Kuipers, S. A. F. T. van Hijum
<span title="2008-04-24">2008</span> <i title="Oxford University Press (OUP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/op7ztx4fhvairowgqifu7dnvsi" style="color: black;">Briefings in Bioinformatics</a> </i> &nbsp;
Based on a comparison of the performance of operon predictions on Escherichia coli and Bacillus subtilis we conclude that there is still room for improvement.  ...  For most organisms, computational operon predictions are the only source of genome-wide operon information.  ...  Other prediction methods have used Bayesian-based techniques [19, 29, 36, 40, 42] , genetic algorithms [35] and machine-learning approaches [26, 39, 41, 44] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1093/bib/bbn019">doi:10.1093/bib/bbn019</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/18420711">pmid:18420711</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lqisclufbvdo7bnhs5b2qxw4xm">fatcat:lqisclufbvdo7bnhs5b2qxw4xm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190223015155/http://pdfs.semanticscholar.org/3ff8/bcdff22a04431861865d7fae41d411f1a502.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3f/f8/3ff8bcdff22a04431861865d7fae41d411f1a502.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1093/bib/bbn019"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> oup.com </button> </a>

Identifying Operons with Deep Neural Networks [article]

Rida Assaf, Fangfang Xia, Rick Stevens
<span title="2019-12-01">2019</span> <i title="Cold Spring Harbor Laboratory"> bioRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
in various studies: E. coli and B. subtilis, with an F1 score of 0.83, outperforming the previously reported state of the art tools.  ...  We propose a new method, which we name Operon Hunter, that uses visual representations of genomic fragments and a residual neural network architecture to make operon predictions.  ...  In addition to HMMs, different machine learning (ML) technologies are deployed for the predition of operons, such as neural networks 24, 25 , support vector machines 26 , and decision tree-based classification  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/860221">doi:10.1101/860221</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iwxurlyehje7tcjffpsyvsml24">fatcat:iwxurlyehje7tcjffpsyvsml24</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200324204822/https://www.biorxiv.org/content/biorxiv/early/2019/12/01/860221.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/54/28/5428ec388b3eea448ff38f7e2eb7eff620a806a9.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/860221"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> biorxiv.org </button> </a>

Gene prediction in metagenomic fragments: A large scale machine learning approach

Katharina J Hoff, Maike Tech, Thomas Lingner, Rolf Daniel, Burkhard Morgenstern, Peter Meinicke
<span title="">2008</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/n5zrklrhlzhtdorf4rk4rmeo3i" style="color: black;">BMC Bioinformatics</a> </i> &nbsp;
Conclusion: Large scale machine learning methods are well-suited for gene prediction in metagenomic DNA fragments.  ...  Results: We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach.  ...  Heiko Liesegang for supporting the development of our method. We are grateful to Andrew Woehler for proofreading the final version of our manuscript.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/1471-2105-9-217">doi:10.1186/1471-2105-9-217</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/18442389">pmid:18442389</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC2409338/">pmcid:PMC2409338</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/f63d4jpihndutayeoqpyui5o6e">fatcat:f63d4jpihndutayeoqpyui5o6e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170830115945/https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/1471-2105-9-217?site=http://bmcbioinformatics.biomedcentral.com" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/cd/ab/cdab84bc863be1808bb5c2cf5768007b1408b99a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/1471-2105-9-217"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2409338" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

COMPUTATIONAL IDENTIFICATION OF PROMOTER REGIONS IN PROKARYOTES AND EUKARYOTES

Sudheer Menon, Shanmughavel Piramanayakam, Gopal Agarwal
<span title="2021-07-09">2021</span> <i title="EPRA JOURNALS"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/aecrfbxhsraafcsha4jh44kx2e" style="color: black;">EPRA International Journal of Agriculture and Rural Economic Research</a> </i> &nbsp;
Therefore, the use of machine learning methods to identify promoters is very important for improving genome annotation and understanding transcriptional regulation.  ...  INDEX TERMS—: deep learning, DNA sequence analysis, Promoter prediction, Promoters, Promoter elements  ...  The E. coli σ70 promoter sequence was extracted from RegulonDB managed manually. The promoter of Bacillus subtilis is from the described collection.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.36713/epra7667">doi:10.36713/epra7667</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wxqohvs3bbhftjv6gqkh7br4lq">fatcat:wxqohvs3bbhftjv6gqkh7br4lq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210715023247/https://eprajournals.com/jpanel/upload/328am_3.EPRA%20JOURNALS%207667.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/8b/ed/8bed69041346cd72e608ac0f8241d9fcbc0a02e6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.36713/epra7667"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

PreCisIon: PREdiction of CIS-regulatory elements improved by gene's positION

Mohamed Elati, Rémy Nicolle, Ivan Junier, David Fernández, Rim Fekih, Julio Font, François Képès
<span title="2012-12-14">2012</span> <i title="Oxford University Press (OUP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hfp6p6inqbdexbsu4r7usndpte" style="color: black;">Nucleic Acids Research</a> </i> &nbsp;
For Bacillus subtilis and Escherichia coli, respectively, PreCisIon achieves on average an area under the receiver operating characteristic curve of 70 and 60%, a sensitivity of 80 and 70% and a specificity  ...  This novel type of information is combined with traditional sequence information by a machine learning algorithm called PreCisIon.  ...  ACKNOWLEDGEMENTS The authors thank Joan He´risson and Marc Schoenauer for their early input into this study. They also thank the anonymous reviewers for their stimulating comments.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1093/nar/gks1286">doi:10.1093/nar/gks1286</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/23241390">pmid:23241390</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC3561985/">pmcid:PMC3561985</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ydfsspkznndi7fv56ol4lv6i4i">fatcat:ydfsspkznndi7fv56ol4lv6i4i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190305143725/http://pdfs.semanticscholar.org/ebb7/3237002a7ef6d3ad83f52f417352d9dd2117.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/eb/b7/ebb73237002a7ef6d3ad83f52f417352d9dd2117.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1093/nar/gks1286"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> oup.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3561985" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Learning the space-time phase diagram of bacterial swarm expansion

Hannah Jeckel, Eric Jelli, Raimo Hartmann, Praveen K. Singh, Rachel Mok, Jan Frederik Totz, Lucia Vidakovic, Bruno Eckhardt, Jörn Dunkel, Knut Drescher
<span title="2019-01-29">2019</span> <i title="Proceedings of the National Academy of Sciences"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nvtuoas5pbdsllkntnhizy4f4q" style="color: black;">Proceedings of the National Academy of Sciences of the United States of America</a> </i> &nbsp;
behavior phases which develop as Bacillus subtilis swarms expand over five orders of magnitude in space.  ...  suitable for multiscale dynamics.  ...  Here, we bridge the gap between gene expression, microscale, and macroscale dynamics by combining an adaptive high-speed microscopy technique with unsupervised machine learning and computational modeling  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1073/pnas.1811722116">doi:10.1073/pnas.1811722116</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wgxtflgrajgidbpqu73n45jixy">fatcat:wgxtflgrajgidbpqu73n45jixy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200321215646/https://www.pnas.org/content/pnas/116/5/1489.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c7/02/c702639780b0d7c9eb875b95067f2cd97c6f2280.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1073/pnas.1811722116"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Promoter Architecture and Promoter Engineering in Saccharomyces cerevisiae

Hongting Tang, Yanling Wu, Jiliang Deng, Nanzhu Chen, Zhaohui Zheng, Yongjun Wei, Xiaozhou Luo, Jay D. Keasling
<span title="2020-08-06">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ie7tehbfsfhs5pdyyt2rrdmnpm" style="color: black;">Metabolites</a> </i> &nbsp;
We also provide a perspective of future directions in this field with an emphasis on the recent advances of machine learning based promoter designs.  ...  Promoters play an essential role in the regulation of gene expression for fine-tuning genetic circuits and metabolic pathways in Saccharomyces cerevisiae (S. cerevisiae).  ...  Based on big data of promoter-protein interactions, machine learning provides a new strategy for rational design and increases the predictability of promoter engineering.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/metabo10080320">doi:10.3390/metabo10080320</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32781665">pmid:32781665</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4yr7mwpnjzenrhdg2wqad7edj4">fatcat:4yr7mwpnjzenrhdg2wqad7edj4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210428231451/https://escholarship.org/content/qt89r1q7t1/qt89r1q7t1.pdf?t=qhcuuv" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f2/8b/f28bff17d9068939dd97bd5a3cca3f7dc34d558b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/metabo10080320"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>
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