Filters








32,442 Hits in 3.3 sec

Deep learning in bioinformatics

Wei Wang, Xin Gao
<span title="2019-06-08">2019</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3jmevtg2ajcdnpgyntimblv7iu" style="color: black;">Methods</a> </i> &nbsp;
The learning process of a neural network is the updating of these connection weights, based on prediction errors made with training data.  ...  The foundation of most modern deep learning models is artificial neural networks.  ...  The method is implemented in a hybrid PAS recognition model (HybPAS), which is based on deep neural networks (DNNs) and logistic regression models (LRMs).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.ymeth.2019.06.006">doi:10.1016/j.ymeth.2019.06.006</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31181259">pmid:31181259</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n4hy4vim6jcl5o2uvxneqnli7m">fatcat:n4hy4vim6jcl5o2uvxneqnli7m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201104170918/https://repository.kaust.edu.sa/bitstream/handle/10754/656346/Deep%20Learning%20in%20Bioinformatics.pdf;jsessionid=C9914B8F915BE4A7F375C49B45373D08?sequence=1" 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/4b/06/4b064b4aad2b4198af710c1922b4ef77cad3de3d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.ymeth.2019.06.006"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Deep Learning Approaches for Protein Structure Prediction

Khatri Chandni, Prof. Mrudang Pandya, Dr. Sunil Jardosh
<span title="2018-09-22">2018</span> <i title="Science Publishing Corporation"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/piy2nrvrjrfcfoz5nmre6zwa4i" style="color: black;">International Journal of Engineering &amp; Technology</a> </i> &nbsp;
In these paper aimed to review work based on protein structure prediction solve using Deep Learning Networks.  ...  In recent years, Machine Learning techniques that are based on Deep Learning networks that show a great promise in research communities.Successful methods for deep learning involve Artificial Neural Networks  ...  [14] in their work that is basically based on Prediction of protein backbone inter-residue angles using Deep Neural Network.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14419/ijet.v7i4.5.20037">doi:10.14419/ijet.v7i4.5.20037</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wppywuzward57nrltevfc6rfsm">fatcat:wppywuzward57nrltevfc6rfsm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190428153143/https://sciencepubco.com/index.php/ijet/article/download/20037/9358" 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/fb/d3/fbd3e669028911d63fc33f8dc5649bfb253b2670.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14419/ijet.v7i4.5.20037"> <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>

Liquified protein vibrations, classification and cross-paradigm de novo image generation using deep neural networks [article]

Markus J. Buehler
<span title="2020-04-16">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
macroscopic images in further processing using deep convolutional neural networks.  ...  Using the DeepDream algorithm, instances of key features of the deep neural network can be made visible in a range of images, allowing us to explore the inner workings of protein surface wave patter neural  ...  Figure 8: An application of DeepDream [39] to generate novel images by activating select layers in the deep neural network, based on the model trained against the water surface images.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2004.07603v1">arXiv:2004.07603v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qudrtyte4nhitayi77ncptluge">fatcat:qudrtyte4nhitayi77ncptluge</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200418003646/https://arxiv.org/ftp/arxiv/papers/2004/2004.07603.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/64/de/64de3dd708594e6643063aef6b3c122066d05e4e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2004.07603v1" 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>

Deep Learning Approach for Secondary Structure Protein Prediction based on First Level Features Extraction using a Latent CNN Structure

Adil Al-Azzawi
<span title="">2017</span> <i title="The Science and Information Organization"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2yzw5hsmlfa6bkafwsibbudu64" style="color: black;">International Journal of Advanced Computer Science and Applications</a> </i> &nbsp;
In this paper, our proposed approach which is a Latent Deep Learning approach relies on detecting the first level features based on using Stacked Sparse Autoencoder.  ...  This approach allows us to detect new features out of the set of training data using the sparse autoencoder which will have used later as convolved filters in the Convolutional Neural Network (CNN) structure  ...  The first one is the unsupervised learning approach based on using Sparse Autoencoder network structure, and the semi-supervised learning approach based on using Deep Learning neural network structure.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14569/ijacsa.2017.080402">doi:10.14569/ijacsa.2017.080402</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xvsujwctdfb6jaosorkheu375y">fatcat:xvsujwctdfb6jaosorkheu375y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170813230139/http://thesai.org/Downloads/Volume8No4/Paper_2-Deep_Learning_Approach_for_Secondary_Structure.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/70/c7/70c7ec6f4753354b2d3302b4ae62aa09e21fa1fa.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14569/ijacsa.2017.080402"> <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>

Deep Learning in the Biomedical Applications: Recent and Future Status

Ryad Zemouri, Noureddine Zerhouni, Daniel Racoceanu
<span title="2019-04-12">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
Deep neural networks represent, nowadays, the most effective machine learning technology in biomedical domain.  ...  In this domain, the different areas of interest concern the Omics (study of the genome—genomics—and proteins—transcriptomics, proteomics, and metabolomics), bioimaging (study of biological cell and tissue  ...  Neural Network and Deep Learning From Shallow to Deep Neural Networks Artificial Neural Networks (ANNs) were inspired in the 1960s by biological neural networks in the brain [11, 12] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app9081526">doi:10.3390/app9081526</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/srjvngtufbhstfcvn4mvhmrdve">fatcat:srjvngtufbhstfcvn4mvhmrdve</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190505231831/https://res.mdpi.com/applsci/applsci-09-01526/article_deploy/applsci-09-01526-v2.pdf?filename=&amp;attachment=1" 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/23/b7/23b7d7a37a37f3d06e8fef0d69b0ac87a8e9b925.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app9081526"> <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>

Computational biology: deep learning

William Jones, Kaur Alasoo, Dmytro Fishman, Leopold Parts
<span title="2017-11-14">2017</span> <i title="Portland Press Ltd."> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zys6voe3srdovn3a4vlajre5h4" style="color: black;">Emerging Topics in Life Sciences</a> </i> &nbsp;
This exciting class of methods, based on artificial neural networks, quickly became popular due to its competitive performance in prediction problems.  ...  Deep learning is the trendiest tool in a computational biologist's toolbox.  ...  Acknowledgements We thank Oliver Stegle for the comments on the text.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1042/etls20160025">doi:10.1042/etls20160025</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33525807">pmid:33525807</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7289034/">pmcid:PMC7289034</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qnw2yndsp5aqlnxxshtaipzctu">fatcat:qnw2yndsp5aqlnxxshtaipzctu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721175323/http://www.emergtoplifesci.org/content/ppetls/1/3/257.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/3e/33/3e33b78552d3cdd5ada3b5960b43463ba15ca235.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1042/etls20160025"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289034" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Deep Learning for Acute Myeloid Leukemia Diagnosis

Elham Nazari, Amir Hossein Farzin, Mehran Aghemiri, Amir Avan, Mahmood Tara, Hamed Tabesh
<span title="">2020</span> <i title="S.C. JURNALUL PENTRU MEDICINA SI VIATA S.R.L"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xytvp3ic75cn7hx7woqgku5eiu" style="color: black;">Journal of Medicine and Life</a> </i> &nbsp;
The results accuracy for single-layer neural network and DNNs deep learning network with three hidden layers are 63.33 and 96.67, respectively.  ...  Then DNNs neural network designed and implemented to the data and finally results cross-validated by classifiers.  ...  Therefore, in this study, deep learning-based techniques and its comparing simple neural network were used to detect AML.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.25122/jml-2019-0090">doi:10.25122/jml-2019-0090</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33072212">pmid:33072212</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7550141/">pmcid:PMC7550141</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xr6suxh3gzcdtftxrcbykmvl4i">fatcat:xr6suxh3gzcdtftxrcbykmvl4i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201029071342/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC7550141&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/5d/85/5d8521bd0fd9b954d18dd05151baefa23d7c02f0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.25122/jml-2019-0090"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7550141" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Novel prediction methods for virtual drug screening [article]

Josip Mesarić
<span title="2022-02-14">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Only in the past few years with increases in computing power have researchers really started to embrace the potential of neural networks in various stages of the drug discovery process.  ...  As these methods are known to demand huge amounts of computational power to get accurate results, prediction models based on machine learning techniques became a popular solution requiring less computational  ...  Feedforward deep neural networks Feedforward deep neural networks (FF-DNNs) are the first and simplest type of neural networks.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2202.06635v1">arXiv:2202.06635v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cab5pvnvw5httnuksmb4ke2piy">fatcat:cab5pvnvw5httnuksmb4ke2piy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220216011006/https://arxiv.org/pdf/2202.06635v1.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/45/02/450254c2485fe4fca203563404353d5ed18d59ad.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2202.06635v1" 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>

Deep Learning and Its Applications in Biomedicine

Chensi Cao, Feng Liu, Hai Tan, Deshou Song, Wenjie Shu, Weizhong Li, Yiming Zhou, Xiaochen Bo, Zhi Xie
<span title="">2018</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/mjqabxhzeveopm6sdbvzz2rmvy" style="color: black;">Genomics, Proteomics &amp; Bioinformatics</a> </i> &nbsp;
Developed from artificial neural networks, deep learning-based algorithms show great promise in extracting features and learning patterns from complex data.  ...  We first introduce the development of artificial neural network and deep learning. We then describe two main components of deep learning, i.e., deep learning architectures and model optimization.  ...  For instance, sequenced-based predictor of protein disorder using boosted ensembles of deep networks (DNdisorder), a deep neural network with multi-layers of RBMs [184] , achieved an average balanced  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.gpb.2017.07.003">doi:10.1016/j.gpb.2017.07.003</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29522900">pmid:29522900</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6000200/">pmcid:PMC6000200</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kennxi3ga5dcpjdtnx27ngvcji">fatcat:kennxi3ga5dcpjdtnx27ngvcji</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200210191400/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC6000200&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/76/44/76444b1a166f41d437fa5ed443244acc518e7d6c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.gpb.2017.07.003"> <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/PMC6000200" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Recent Applications of Deep Learning Methods on Evolution- and Contact-Based Protein Structure Prediction

Donghyuk Suh, Jai Woo Lee, Sun Choi, Yoonji Lee
<span title="2021-06-02">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3loumxx7kzamnlu4h6x3xoz6ay" style="color: black;">International Journal of Molecular Sciences</a> </i> &nbsp;
Especially, methods employing deep neural networks have had a significant impact on recent CASP13 and CASP14 competition.  ...  The prediction of proteins' 3D structural components is now heavily dependent on machine learning techniques that interpret how protein sequences and their homology govern the inter-residue contacts and  ...  SPOT-Disorder2 offers per-residue disorder prediction based on a deep neural network utilizing LSTM cells [64] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/ijms22116032">doi:10.3390/ijms22116032</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34199677">pmid:34199677</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8199773/">pmcid:PMC8199773</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7znk2khhhfgj7err5roqnygz6i">fatcat:7znk2khhhfgj7err5roqnygz6i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210606030621/https://res.mdpi.com/d_attachment/ijms/ijms-22-06032/article_deploy/ijms-22-06032-v2.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/59/b6/59b65e9890442a5c5f223ea6e43f55128e7f08fd.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/ijms22116032"> <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> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199773" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Deep Learning in Bioinformatics [article]

Seonwoo Min, Byunghan Lee, Sungroh Yoon
<span title="2016-06-19">2016</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
., omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e., deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures)  ...  In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics.  ...  Lapse detection from EEG signal with a recurrent neural network [178] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1603.06430v5">arXiv:1603.06430v5</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xvgg7misrrcsxmshty2emnujaq">fatcat:xvgg7misrrcsxmshty2emnujaq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191013050923/https://arxiv.org/pdf/1603.06430v5.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/60/77/60773264d38a258e3e34c8b933ec2e5b00b5dc55.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1603.06430v5" 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>

A deep learning framework for improving protein interaction prediction using sequence properties [article]

Yi Guo, Xiang Chen
<span title="2019-11-15">2019</span> <i title="Cold Spring Harbor Laboratory"> bioRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
and compositions of protein sequence into a unified prediction framework using a hybrid deep neural network.  ...  Results: We have developed a deep learning-based framework, named iPPI, for accurately predicting PPI on a proteome-wide scale depended only on sequence information. iPPI integrates the amino acid properties  ...  After that, a hybrid deep neural network ܰ is trained based on each dataset ‫ܤ‬ independently, resulting in an ensemble of binary classifiers ሼ ܰ ሽ .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/843755">doi:10.1101/843755</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/s6kmsw3nkzh4tapedqbzpczyau">fatcat:s6kmsw3nkzh4tapedqbzpczyau</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200213174145/https://www.biorxiv.org/content/biorxiv/early/2019/11/15/843755.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] </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/843755"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> biorxiv.org </button> </a>

Deep Learning for Anomaly Detection: A Survey [article]

Raghavendra Chalapathy (University of Sydney and Capital Markets Cooperative Research Centre, Sanjay Chawla (Qatar Computing Research Institute
<span title="2019-01-23">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The aim of this survey is two-fold, firstly we present a structured and comprehensive overview of research methods in deep learning-based anomaly detection.  ...  We have grouped state-of-the-art research techniques into different categories based on the underlying assumptions and approach adopted.  ...  One-Class Neural Networks (OC-NN) One class neural network (OC-NN) Chalapathy et al. [2018a] methods are inspired by kernel-based one-class classification which combines the ability of deep networks  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1901.03407v2">arXiv:1901.03407v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/x3tb4ccxfvdkfo7k2y2oxhr7ly">fatcat:x3tb4ccxfvdkfo7k2y2oxhr7ly</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200824174638/https://arxiv.org/pdf/1901.03407v2.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/d4/df/d4df464de69fae2b2179718046a17edc51f7d68f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1901.03407v2" 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>

2020 Index IEEE/ACM Transactions on Computational Biology and Bioinformatics Vol. 17

<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q75ftrlivrhrnno5ijjuyufx5a" style="color: black;">IEEE/ACM Transactions on Computational Biology &amp; Bioinformatics</a> </i> &nbsp;
-Oct. 2020 1573-1581 Complex networks Disruption of Protein Complexes from Weighted Complex Networks. Habibi, M., +, TCBB Jan.  ...  ., +, TCBB May-June 2020 887-898 Detection of Colorectal Carcinoma Based on Microbiota Analysis Using Generalized Regression Neural Networks and Nonlinear Feature Selection.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tcbb.2020.3047571">doi:10.1109/tcbb.2020.3047571</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/x3kmrpexsve6bnjtd3dh6ntkyy">fatcat:x3kmrpexsve6bnjtd3dh6ntkyy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210717221448/https://ieeexplore.ieee.org/ielx7/8857/9346082/09346083.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/4c/f3/4cf310456a9de26c7df0479c8de3cbf758b3ba29.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tcbb.2020.3047571"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Deep Learning for Genomics: A Concise Overview [article]

Tianwei Yue, Haohan Wang
<span title="2018-05-08">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
A powerful deep learning model should rely on insightful utilization of task-specific knowledge.  ...  In this paper, we briefly discuss the strengths of different deep learning models from a genomic perspective so as to fit each particular task with a proper deep architecture, and remark on practical considerations  ...  A collaboratively written review paper on deep learning, genomics, and precision medicine, now available at https://greenelab.github.io/deep-review/  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1802.00810v2">arXiv:1802.00810v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/u6s7pz2p6jdxzodz5k34it2hiu">fatcat:u6s7pz2p6jdxzodz5k34it2hiu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191023055258/https://arxiv.org/pdf/1802.00810v2.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/12/ea/12ea15e4a20105e52410b460964561e34234b977.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1802.00810v2" 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>
&laquo; Previous Showing results 1 &mdash; 15 out of 32,442 results