A citation-based method for searching scientific literature

S Hochreiter, J Schmidhuber. Neural Comput 1997
Times Cited: 2814







List of co-cited articles
133 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
15

Learning long-term dependencies with gradient descent is difficult.
Y Bengio, P Simard, P Frasconi. IEEE Trans Neural Netw 1994
440
14

LSTM: A Search Space Odyssey.
Klaus Greff, Rupesh K Srivastava, Jan Koutnik, Bas R Steunebrink, Jurgen Schmidhuber. IEEE Trans Neural Netw Learn Syst 2017
196
10


Deep learning in neural networks: an overview.
Jürgen Schmidhuber. Neural Netw 2015
5

Learning to forget: continual prediction with LSTM.
F A Gers, J Schmidhuber, F Cummins. Neural Comput 2000
227
5

MIMIC-III, a freely accessible critical care database.
Alistair E W Johnson, Tom J Pollard, Lu Shen, Li-Wei H Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, Roger G Mark. Sci Data 2016
4

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.
S F Altschul, T L Madden, A A Schäffer, J Zhang, Z Zhang, W Miller, D J Lipman. Nucleic Acids Res 1997
4

Automated EEG-based screening of depression using deep convolutional neural network.
U Rajendra Acharya, Shu Lih Oh, Yuki Hagiwara, Jen Hong Tan, Hojjat Adeli, D P Subha. Comput Methods Programs Biomed 2018
70
5

A novel connectionist system for unconstrained handwriting recognition.
Alex Graves, Marcus Liwicki, Santiago Fernández, Roman Bertolami, Horst Bunke, Jürgen Schmidhuber. IEEE Trans Pattern Anal Mach Intell 2009
88
3

Mastering the game of Go with deep neural networks and tree search.
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot,[...]. Nature 2016
884
3

Application of Generative Autoencoder in De Novo Molecular Design.
Thomas Blaschke, Marcus Olivecrona, Ola Engkvist, Jürgen Bajorath, Hongming Chen. Mol Inform 2018
104
3

Extended-connectivity fingerprints.
David Rogers, Mathew Hahn. J Chem Inf Model 2010
3

DrugBank: a knowledgebase for drugs, drug actions and drug targets.
David S Wishart, Craig Knox, An Chi Guo, Dean Cheng, Savita Shrivastava, Dan Tzur, Bijaya Gautam, Murtaza Hassanali. Nucleic Acids Res 2008
3

ACP-DL: A Deep Learning Long Short-Term Memory Model to Predict Anticancer Peptides Using High-Efficiency Feature Representation.
Hai-Cheng Yi, Zhu-Hong You, Xi Zhou, Li Cheng, Xiao Li, Tong-Hai Jiang, Zhan-Heng Chen. Mol Ther Nucleic Acids 2019
30
10


Automated detection of COVID-19 cases using deep neural networks with X-ray images.
Tulin Ozturk, Muhammed Talo, Eylul Azra Yildirim, Ulas Baran Baloglu, Ozal Yildirim, U Rajendra Acharya. Comput Biol Med 2020
312
3

Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks.
Ali Abbasian Ardakani, Alireza Rajabzadeh Kanafi, U Rajendra Acharya, Nazanin Khadem, Afshin Mohammadi. Comput Biol Med 2020
118
3

Prediction and analysis of COVID-19 positive cases using deep learning models: A descriptive case study of India.
Parul Arora, Himanshu Kumar, Bijaya Ketan Panigrahi. Chaos Solitons Fractals 2020
49
6


Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.
U Rajendra Acharya, Shu Lih Oh, Yuki Hagiwara, Jen Hong Tan, Hojjat Adeli. Comput Biol Med 2018
223
3


A deep learning framework for automatic diagnosis of unipolar depression.
Wajid Mumtaz, Abdul Qayyum. Int J Med Inform 2019
13
23

Dermatologist-level classification of skin cancer with deep neural networks.
Andre Esteva, Brett Kuprel, Roberto A Novoa, Justin Ko, Susan M Swetter, Helen M Blau, Sebastian Thrun. Nature 2017
3

Time series forecasting of Covid-19 using deep learning models: India-USA comparative case study.
Sourabh Shastri, Kuljeet Singh, Sachin Kumar, Paramjit Kour, Vibhakar Mansotra. Chaos Solitons Fractals 2020
18
16

Deep learning-based electroencephalography analysis: a systematic review.
Yannick Roy, Hubert Banville, Isabela Albuquerque, Alexandre Gramfort, Tiago H Falk, Jocelyn Faubert. J Neural Eng 2019
89
3

Improved protein structure prediction using potentials from deep learning.
Andrew W Senior, Richard Evans, John Jumper, James Kirkpatrick, Laurent Sifre, Tim Green, Chongli Qin, Augustin Žídek, Alexander W R Nelson, Alex Bridgland,[...]. Nature 2020
400
3

Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach.
Thomas Desautels, Jacob Calvert, Jana Hoffman, Melissa Jay, Yaniv Kerem, Lisa Shieh, David Shimabukuro, Uli Chettipally, Mitchell D Feldman, Chris Barton,[...]. JMIR Med Inform 2016
141
2

The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).
Mervyn Singer, Clifford S Deutschman, Christopher Warren Seymour, Manu Shankar-Hari, Djillali Annane, Michael Bauer, Rinaldo Bellomo, Gordon R Bernard, Jean-Daniel Chiche, Craig M Coopersmith,[...]. JAMA 2016
2

Multitask learning and benchmarking with clinical time series data.
Hrayr Harutyunyan, Hrant Khachatrian, David C Kale, Greg Ver Steeg, Aram Galstyan. Sci Data 2019
56
3

The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances.
Anthony Bagnall, Jason Lines, Aaron Bostrom, James Large, Eamonn Keogh. Data Min Knowl Discov 2017
47
4

Association mapping in biomedical time series via statistically significant shapelet mining.
Christian Bock, Thomas Gumbsch, Michael Moor, Bastian Rieck, Damian Roqueiro, Karsten Borgwardt. Bioinformatics 2018
7
28

Molecular generative model based on conditional variational autoencoder for de novo molecular design.
Jaechang Lim, Seongok Ryu, Jin Woo Kim, Woo Youn Kim. J Cheminform 2018
49
4

ChEMBL: a large-scale bioactivity database for drug discovery.
Anna Gaulton, Louisa J Bellis, A Patricia Bento, Jon Chambers, Mark Davies, Anne Hersey, Yvonne Light, Shaun McGlinchey, David Michalovich, Bissan Al-Lazikani,[...]. Nucleic Acids Res 2012
2


Generative Recurrent Networks for De Novo Drug Design.
Anvita Gupta, Alex T Müller, Berend J H Huisman, Jens A Fuchs, Petra Schneider, Gisbert Schneider. Mol Inform 2018
109
2

Molecular de-novo design through deep reinforcement learning.
Marcus Olivecrona, Thomas Blaschke, Ola Engkvist, Hongming Chen. J Cheminform 2017
189
2

Adversarial Threshold Neural Computer for Molecular de Novo Design.
Evgeny Putin, Arip Asadulaev, Quentin Vanhaelen, Yan Ivanenkov, Anastasia V Aladinskaya, Alex Aliper, Alex Zhavoronkov. Mol Pharm 2018
50
4

Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks.
Marwin H S Segler, Thierry Kogej, Christian Tyrchan, Mark P Waller. ACS Cent Sci 2018
273
2

How to improve R&D productivity: the pharmaceutical industry's grand challenge.
Steven M Paul, Daniel S Mytelka, Christopher T Dunwiddie, Charles C Persinger, Bernard H Munos, Stacy R Lindborg, Aaron L Schacht. Nat Rev Drug Discov 2010
2

Deep reinforcement learning for de novo drug design.
Mariya Popova, Olexandr Isayev, Alexander Tropsha. Sci Adv 2018
195
2

De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping.
Boris Sattarov, Igor I Baskin, Dragos Horvath, Gilles Marcou, Esben Jannik Bjerrum, Alexandre Varnek. J Chem Inf Model 2019
31
6

Dependency-based long short term memory network for drug-drug interaction extraction.
Wei Wang, Xi Yang, Canqun Yang, Xiaowei Guo, Xiang Zhang, Chengkun Wu. BMC Bioinformatics 2017
16
12

Wearable Fall Detector Using Recurrent Neural Networks.
Francisco Luna-Perejón, Manuel Jesús Domínguez-Morales, Antón Civit-Balcells. Sensors (Basel) 2019
10
20

Protein Phosphorylation: A Major Switch Mechanism for Metabolic Regulation.
Sean J Humphrey, David E James, Matthias Mann. Trends Endocrinol Metab 2015
191
2

MusiteDeep: a deep-learning framework for general and kinase-specific phosphorylation site prediction.
Duolin Wang, Shuai Zeng, Chunhui Xu, Wangren Qiu, Yanchun Liang, Trupti Joshi, Dong Xu. Bioinformatics 2017
70
2

DeepPhos: prediction of protein phosphorylation sites with deep learning.
Fenglin Luo, Minghui Wang, Yu Liu, Xing-Ming Zhao, Ao Li. Bioinformatics 2019
34
5

A fast learning algorithm for deep belief nets.
Geoffrey E Hinton, Simon Osindero, Yee-Whye Teh. Neural Comput 2006
2

Recurrent Neural Network for Predicting Transcription Factor Binding Sites.
Zhen Shen, Wenzheng Bao, De-Shuang Huang. Sci Rep 2018
37
5

Musite, a tool for global prediction of general and kinase-specific phosphorylation sites.
Jianjiong Gao, Jay J Thelen, A Keith Dunker, Dong Xu. Mol Cell Proteomics 2010
159
2


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.