ArticleBioMed research international2016
A Prediction Model for Membrane Proteins Using Moments Based Features.
Article in BioMed research international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Machine learning driven dashboard for chronic myeloid leukemia prediction using protein sequences.PloS one · 2025Article
- Hybrid framework for membrane protein type prediction based on the PSSM.Scientific reports · 2024Article
- A Framework for Prediction of Oncogenomic Progression Aiding Personalized Treatment of Gastric Cancer.Diagnostics (Basel, Switzerland) · 2023Article
- Ensemble Learning for Hormone Binding Protein Prediction: A Promising Approach for Early Diagnosis of Thyroid Hormone Disorders in Serum.Diagnostics (Basel, Switzerland) · 2023Article
- Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications.Computational and structural biotechnology journal · 2023Review
- IGPred-HDnet: Prediction of Immunoglobulin Proteins Using Graphical Features and the Hierarchal Deep Learning-Based Approach.Computational intelligence and neuroscience · 2023Article
- A machine learning technique for identifying DNA enhancer regions utilizing CIS-regulatory element patterns.Scientific reports · 2022Article
- iAcety-SmRF: Identification of Acetylation Protein by Using Statistical Moments and Random Forest.Membranes · 2022Article
- Article
- An analytical study on the identification of N-linked glycosylation sites using machine learning model.PeerJ. Computer science · 2022Article
- Identification of stress response proteins through fusion of machine learning models and statistical paradigms.Scientific reports · 2021Article
- iTAGPred: A Two-Level Prediction Model for Identification of Angiogenesis and Tumor Angiogenesis Biomarkers.Applied bionics and biomechanics · 2021Article
- iSUMOK-PseAAC: prediction of lysine sumoylation sites using statistical moments and Chou's PseAAC.PeerJ · 2021Article
- Integrative approach for detecting membrane proteins.BMC bioinformatics · 2020Article
- Identification of 4-carboxyglutamate residue sites based on position based statistical feature and multiple classification.Scientific reports · 2020Article
- iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical MomentsCurrent genomics · 2019Article
- iMethylK_pseAAC: Improving Accuracy of Lysine Methylation Sites Identification by Incorporating Statistical Moments and Position Relative Features into General PseAACCurrent genomics · 2019Article
- Predicting membrane proteins and their types by extracting various sequence features into Chou's general PseAAC.Molecular biology reports · 2018Article
- iPhosY-PseAAC: identify phosphotyrosine sites by incorporating sequence statistical moments into PseAAC.Molecular biology reports · 2018Article
- A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.Scientific reports · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The most expedient unit of the human body is its cell. Encapsulated within the cell are many infinitesimal entities and molecules which are protected by a cell membrane. The proteins that are associated with this lipid based bilayer cell membrane are known as membrane proteins and are considered to play a significant role. These membrane proteins exhibit their effect in cellular activities inside and outside of the cell. According to the scientists in pharmaceutical organizations, these membrane proteins perform key task in drug interactions. In this study, a technique is presented that is based on various computationally intelligent methods used for the prediction of membrane protein without the experimental use of mass spectrometry. Statistical moments were used to extract features and furthermore a Multilayer Neural Network was trained using backpropagation for the prediction of membrane proteins. Results show that the proposed technique performs better than existing methodologies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.