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A Protein Interaction Verification System Based on a Neural Network Algorithm

Min Su Lee, Seung Soo Park, Min Kyung Kim
2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)  
The system is based on a neural network algorithm, and utilizes three characteristics of interacting proteins: 1) interacting proteins share similar functional category, 2) interacting proteins must locate  ...  We developed a new reliability assessment system for protein-protein interaction dataset of yeast that can identify real interacting protein pairs from noisy dataset.  ...  The system uses a neural network algorithm based on the three characteristics of interacting proteins. First, interacting proteins share similar functional category.  ... 
doi:10.1109/csbw.2005.15 dblp:conf/csb/LeePK05 fatcat:rxworiadinbohcisgnfz2mnudq

Identification of Feature Genes of a Novel Neural Network Model for Bladder Cancer

Yongqing Zhang, Shan Hua, Qiheng Jiang, Zhiwen Xie, Lei Wu, Xinjie Wang, Fei Shi, Shengli Dong, Juntao Jiang
2022 Frontiers in Genetics  
Based on the random forest algorithm, we selected 14 feature genes to construct the neural network model.  ...  Consequently, we utilized a random forest algorithm to identify feature genes and further constructed a neural network model.  ...  Construction and Verification of the Neural Network Model Based on the scores and weights of the feature gene list, we constructed a novel neural network model to predict whether the sample belonged to  ... 
doi:10.3389/fgene.2022.912171 pmid:35719407 pmcid:PMC9198295 fatcat:6yzlgudzr5b45kztygsz4cswbm

High-Throughput Self-Interaction Chromatography: Applications in Protein Formulation Prediction

David H. Johnson, Arun Parupudi, W. William Wilson, Lawrence J. DeLucas
2008 Pharmaceutical Research  
Demonstrate the ability of an artificial neural network (ANN), trained on a formulation screen of measured second virial coefficients to predict protein self-interactions for untested formulation conditions  ...  As a measure of protein-protein interactions correlated with solubility, B 22 value predictions based on a small screen may enable rapid determination of high solubility formulations.  ...  ACKNOWLEDGEMENTS This work was supported by a grant from the NSF EPSCoR Graduate Research Scholars Program. Thank you to Dr. Lisa Nagy for help with the Shimadzu HPLC hardware.  ... 
doi:10.1007/s11095-008-9737-6 pmid:18923812 fatcat:hwudcyxq6zcr3cixb2nozs4xyu

A Two-Step Strategy for the Search for Ligands for Target Proteins

Eugene Alexandrovich Borodin, Natalya Yurievna Leusova, Alexander Pavlovich Chupalov, Pavel Dmitrievich Timkin, Eduard Andreevich Timofeev, Victor Pavlovich Kolosov, Juliy Mikhailovich Perelman
2021 International Journal of Pharmaceutical and Phytopharmacological Research  
In the present study, we used the example of the search for ligands for the nonselective cationic channel TRPM8 to propose a two-step strategy based on deep neural networks and further verification by  ...  The strategy consists of using a neural network to screen out potential drug candidates and thereby reduce the list of candidate ligands for verification by intermolecular AutoDock program, which allows  ...  CONCLUSION In the present study, we proposed a strategy for predicting potential ligands for TRPM8 in silico, based on the use of machine learning tools based on deep neural networks and further verification  ... 
doi:10.51847/893brcef1g fatcat:7xjde32tozgzpelnu5a7l2paba

Refining the Undecidability Frontier of Hybrid Automata [chapter]

Venkatesh Mysore, Amir Pnueli
2005 Lecture Notes in Computer Science  
neural-network-based tool and developed a SVM-based tool for predicting DNA-binding residues in proteins, working with Prof.  ...  the real Turing machine formalism Analyzing several biochemical pathways including the cell cycle, delta-notch and bacterial chemotaxis protein-interaction systems  Developing a new framework for modeling  ... 
doi:10.1007/11590156_21 fatcat:7c57b3zny5bn5bgeesy2ck25w4

A High Efficient Biological Language Model for Predicting Protein–Protein Interactions

Yanbin Wang, Zhu-Hong You, Shan Yang, Xiao Li, Tong-Hai Jiang, Xi Zhou
2019 Cells  
The model was constructed based on a feature representation method for biological sequences called bio-to-vector (Bio2Vec) and a convolution neural network (CNN).  ...  In this paper, a pure biological language processing model is proposed for predicting proteinprotein interactions only using a protein sequence.  ...  [16] . we arranged 36,630 interacting protein pairs based on the information at the database, and 36,480 non-interacting protein pairs based on the scheme mentioned above.  ... 
doi:10.3390/cells8020122 pmid:30717470 pmcid:PMC6406841 fatcat:iqqdcts5obbdrhk5krj5fnclhe

Feature Genes in Neuroblastoma Distinguishing High-Risk and Non-high-Risk Neuroblastoma Patients: Development and Validation Combining Random Forest With Artificial Neural Network

Sha Yang, Lingfeng Zeng, Xin Jin, Huapeng Lin, Jianning Song
2022 Frontiers in Medicine  
on the random forest (RF) algorithm and artificial neural network (ANN) algorithm.  ...  The prediction model based on gene expression data in this study showed high overall accuracy and precision in both the training set and the test set (AUC = 0.998 in GSE49710 and AUC = 0.858 in GSE73517  ...  Construction of Protein-Protein Interaction Network STRING database 3 (24) was used to construct the Protein-Protein Interaction (PPI) network to analyze the functional interactions of DEGs.  ... 
doi:10.3389/fmed.2022.882348 pmid:35911385 pmcid:PMC9336509 fatcat:dfhzrnf3sbdthklhsasc3o4ynq

Derin Öğrenme Araştırma Alanlarının Literatür Taraması

M. Mutlu Yapıcı, Adem Tekerek, Nurettin Topaloğlu
2019 Gazi Mühendislik Bilimleri Dergisi  
Çalışmada Özerk Araçlar (Autonomous Vehicles), Doğal Dil İşleme (Natural Language Processing), El Yazısı Karakter Tanıma (Handwritten Character Recognition), İmza Doğrulama (Signature Verification), Ses  ...  This study investigated DL studies which are made in the most popular and challenging fields such as autonomous vehicles, natural language processing, handwritten character recognition, signature verification  ...  Hence recently many researchers study to predict protein-protein interaction.  ... 
doi:10.30855/gmbd.2019.03.01 fatcat:2sv7dg7elrfqppcjx5otzmb7pi

Protein secondary structure prediction by a neural network architecture with simple positioning algorithm techniques

Romana Rahman Ema, Sharmin Sultana, Shakil Ahmed Shaj, Syed Md. Galib
2022 International Journal of Power Electronics and Drive Systems (IJPEDS)  
In this paper, an innovative method has been proposed for predicting protein secondary structures based on 3-state protein secondary structure by neural network architecture with simple positioning algorithm  ...  Finally using a new method of neural network, it is verified that the Q3 prediction method gives good results from the neural network approach.  ...  Neural network approaches Neural network allows one more approach to apprehend more sophisticated residue interactivity.  ... 
doi:10.11591/ijece.v12i4.pp4380-4390 fatcat:soxgngwnfbexxmoce3hjbaumjq

Link Prediction using Graph Neural Networks for Master Data Management [article]

Balaji Ganesan, Srinivas Parkala, Neeraj R Singh, Sumit Bhatia, Gayatri Mishra, Matheen Ahmed Pasha, Hima Patel, Somashekar Naganna
2020 arXiv   pre-print
Predicting links between people using Graph Neural Networks requires careful ethical and privacy considerations than in domains where GNNs have typically been applied so far.  ...  Contact tracing of COVID19 positive persons could also be posed as a Link Prediction problem.  ...  [6] introduced the Protein-Protein Interaction dataset which has been used in a number of recent works in graph neural networks. [cite] presented Graph Convolutional networks.  ... 
arXiv:2003.04732v2 fatcat:qfak6f4265gerl7yvj36nbl444

Intelligent Informatics in Translational Medicine 2016

Hao-Teng Chang, Tatsuya Akutsu, Oliver Ray, Sorin Draghici, Tun-Wen Pai
2017 BioMed Research International  
We also want to thank all reviewers and editors for their hard work on this issue. Hao-Teng Chang Tatsuya Akutsu Oliver Ray Sorin Draghici Tun-Wen Pai  ...  The authors have evaluated the proposed model on two biomedical relation extraction tasks including drugdrug interaction extraction and protein-protein interaction extraction.  ...  Li et al. constructed a multilevel evolutionary structure for avian influenza virus system based on considering both hemagglutinin and neuraminidase protein fragments.  ... 
doi:10.1155/2017/1572730 pmid:28337442 pmcid:PMC5350342 fatcat:yrp3n5wmujbq5ooyoq5f42bxzu

The Application of Artificial Intelligence in the Genetic Study of Alzheimer's Disease

Rohan Mishra, Bin Li
2020 Aging and Disease  
expression profile, gene-gene interaction in AD, and genetic analysis of AD based on a knowledge base.  ...  Then, a comprehensive review is focused on the application of AI in the genetic research of AD, including the diagnosis and prognosis of AD based on genetic data, the analysis of genetic variation, gene  ...  Zafeiris et al. designed an integrated artificial neural network (ANN) pipeline for biomarker discovery and verification in AD.  ... 
doi:10.14336/ad.2020.0312 pmid:33269107 pmcid:PMC7673858 fatcat:72rkx7bjvbaf7earfiu5d44rqm

Overview of BITS2005, the Second Annual Meeting of the Italian Bioinformatics Society

Manuela Helmer-Citterich, Rita Casadio, Alessandro Guffanti, Giancarlo Mauri, Luciano Milanesi, Graziano Pesole, Giorgio Valle, Cecilia Saccone
2005 BMC Bioinformatics  
An inferred human protein interaction network was built by Persico et al. [22] , based on the identification of reliable orthologues of proteins known to interact in a number of reference sets.  ...  on a "structure-to-structure" prediction, by means of an artificial neural network.  ... 
doi:10.1186/1471-2105-6-s4-s1 fatcat:xnqmjj5nurendicaf4hbbde7ka

Prediction Methods of Herbal Compounds in Chinese Medicinal Herbs

Ke Han, Lei Zhang, Miao Wang, Rui Zhang, Chunyu Wang, Chengzhi Zhang
2018 Molecules  
A growing number of Chinese herbal source compounds are now widely used as drug-like compound candidates.  ...  In this paper, we focus on the prediction methods for the medicinal properties of Chinese herbal medicines.  ...  have established a network model based on recursive partitioning algorithms based on 3117 drugs and 2238 non-pharmaceuticals, but the effect is not particularly ideal [82] used a variety of different  ... 
doi:10.3390/molecules23092303 pmid:30201875 pmcid:PMC6225236 fatcat:juaipuzpova7pjy5ipcom37f4u

Characterization and Prediction of Protein Interfaces to Infer Protein-Protein Interaction Networks

Ozlem Keskin, Nurcan Tuncbag, Attila Gursoy
2008 Current Pharmaceutical Biotechnology  
Complex protein-protein interaction networks govern biological processes in cells. Protein interfaces are the sites where proteins physically interact.  ...  Thus, understanding biological processes relies on a comprehensive knowledge of different types of proteinprotein interactions and interaction mechanisms [1].  ...  The algorithm is a structure based method.  ... 
doi:10.2174/138920108783955191 pmid:18393863 fatcat:dt5tuv2hurejbh3olvgnegpx7i
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