ArticleComputational and mathematical methods in medicine2021
Genomic Island Prediction via Chi-Square Test and Random Forest Algorithm.
Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20 citing papers in PubMed, 44 citations in OpenAlex.
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- MSFC: a new feature construction method for accurate diagnosis of mass spectrometry data.Scientific reports · 2023Article
- Using the Random Forest for Identifying Key Physicochemical Properties of Amino Acids to Discriminate Anticancer and Non-Anticancer Peptides.International journal of molecular sciences · 2023Article
- Identification of genes related to immune enhancement caused by heterologous ChAdOx1-BNT162b2 vaccines in lymphocytes at single-cell resolution with machine learning methods.Frontiers in immunology · 2023Article
- Identification of Transcriptome Biomarkers for Severe COVID-19 with Machine Learning Methods.Biomolecules · 2022Article
- MPMABP: A CNN and Bi-LSTM-Based Method for Predicting Multi-Activities of Bioactive Peptides.Pharmaceuticals (Basel, Switzerland) · 2022Article
- CNNLSTMac4CPred: A Hybrid Model for N4-Acetylcytidine Prediction.Interdisciplinary sciences, computational life sciences · 2022Article
- Identification of Two CDK5R1-Related Subtypes and Characterization of Immune Infiltrates in Alzheimer's Disease Based on an Integrated Bioinformatics Analysis.Computational and mathematical methods in medicine · 2022Article
- Identification of methylation signatures and rules for predicting the severity of SARS-CoV-2 infection with machine learning methods.Frontiers in microbiology · 2022Article
- Identification of methylation signatures associated with CAR T cell in B-cell acute lymphoblastic leukemia and non-hodgkin's lymphoma.Frontiers in oncology · 2022Article
- Identifying anal and cervical tumorigenesis-associated methylation signaling with machine learning methods.Frontiers in oncology · 2022Article
- Gm-PLoc: A Subcellular Localization Model of Multi-Label Protein Based on GAN and DeepFM.Frontiers in genetics · 2022Article
- Identification of Type 2 Diabetes Biomarkers From Mixed Single-Cell Sequencing Data With Feature Selection Methods.Frontiers in bioengineering and biotechnology · 2022Article
- Identifying Functions of Proteins in Mice With Functional Embedding Features.Frontiers in genetics · 2022Article
- Mathematical Modeling and Computational Prediction of High-Risk Types of Human Papillomaviruses.Computational and mathematical methods in medicine · 2022Article
- Predicting RNA 5-Methylcytosine Sites by Using Essential Sequence Features and Distributions.BioMed research international · 2022Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genomic islands are related to microbial adaptation and carry different genomic characteristics from the host. Therefore, many methods have been proposed to detect genomic islands from the rest of the genome by evaluating its sequence composition. Many sequence features have been proposed, but many of them have not been applied to the identification of genomic islands. In this paper, we present a scheme to predict genomic islands using the chi-square test and random forest algorithm. We extract seven kinds of sequence features and select the important features with the chi-square test. All the selected features are then input into the random forest to predict the genome islands. Three experiments and comparison show that the proposed method achieves the best performance. This understanding can be useful to design more powerful method for the genomic island prediction.
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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.