4.7 Article

iTTCA-RF: a random forest predictor for tumor T cell antigens

Related references

Note: Only part of the references are listed.
Review Biochemical Research Methods

Application of deep learning methods in biological networks

Shuting Jin et al.

Summary: The increase in biological data and the formation of biomolecule interaction databases have led to the emergence of diverse biological networks, providing valuable resources for understanding biological systems, complex disease discovery, and drug research. However, the complexity of biological networks analysis has also increased with the rise in data volume, necessitating algorithms like deep learning to handle large, heterogeneous, and complex data. Deep learning, with its ability to extract abstract features and process complex graph data structures, is increasingly being used in mining valuable information from network data.

BRIEFINGS IN BIOINFORMATICS (2021)

Article Biochemical Research Methods

FoldRec-C2C: protein fold recognition by combining cluster-to-cluster model and protein similarity network

Jiangyi Shao et al.

Summary: The FoldRec-C2C predictor globally incorporates protein interactions for protein fold recognition, treating it as an information retrieval task in natural language processing. Tested on the LINDAHL dataset, FoldRec-C2C outperforms 34 state-of-the-art methods in the field.

BRIEFINGS IN BIOINFORMATICS (2021)

Article Biochemical Research Methods

Deep-Kcr: accurate detection of lysine crotonylation sites using deep learning method

Hao Lv et al.

Summary: In this study, a deep learning-based method called Deep-Kcr was developed for predicting Kcr sites by combining various features and using CNN as a classifier, which showed high computational efficiency on large datasets. The Deep-Kcr method demonstrated excellent predictive power and robustness when compared with other existing tools, and a webserver was established for its free access.

BRIEFINGS IN BIOINFORMATICS (2021)

Article Biochemical Research Methods

ProtFold-DFG: protein fold recognition by combining Directed Fusion Graph and PageRank algorithm

Jiangyi Shao et al.

Summary: This study introduces a network-based predictor ProtFold-DFG for protein fold recognition, utilizing Directed Fusion Graph (DFG), KL divergence, and PageRank algorithm to enhance recognition accuracy. Experimental results demonstrate that ProtFold-DFG outperforms 35 other methods on the LINDAHL dataset, making it a promising approach for protein fold recognition.

BRIEFINGS IN BIOINFORMATICS (2021)

Article Biochemical Research Methods

Prediction of drug response in multilayer networks based on fusion of multiomics data

Liang Yu et al.

Summary: The study introduced a new method named DREMO, which predicts the response of cancer cell lines to therapeutic agents by integrating multiomics data and using machine learning models. Through construction of a multilayer similarity network and validation with established databases, literature, and functional pathway database, it was shown that DREMO significantly improves predictive capabilities compared to other methods.

METHODS (2021)

Article Biochemical Research Methods

SubtypeDrug: a software package for prioritization of candidate cancer subtype-specific drugs

Xudong Han et al.

Summary: SubtypeDrug is a software package based on systems biology that prioritizes subtype-specific drugs based on cancer expression data from samples of multiple subtypes. It uses a novel approach to identify subtype-specific drugs by considering the biological functions regulated by drugs at the subpathway level. Its capabilities include extraction of subpathways from biological pathways, identification of dysregulated subpathways induced by each drug, inference of sample-specific subpathway activity profiles, evaluation of drug-disease reverse association at the subpathway level, identification of cancer-subtype-specific drugs through subtype sample set enrichment analysis, and visualization of the results.

BIOINFORMATICS (2021)

Article Medicine, General & Internal

rs1990622 variant associates with Alzheimer's disease and regulates TMEM106B expression in human brain tissues

Yang Hu et al.

Summary: The study revealed that the TMEM106B gene rs1990622 variant T allele increased the risk of Alzheimer's disease (AD), particularly in females; TMEM106B showed differential expression in different human brain tissues with high expression in the cerebellum; the rs1990622 variant could regulate TMEM106B expression in human brain tissues, with colocalization analysis supporting its impact on AD risk and TMEM106B expression.

BMC MEDICINE (2021)

Article Biochemical Research Methods

ITP-Pred: an interpretable method for predicting, therapeutic peptides with fused features low-dimension representation

Lijun Cai et al.

Summary: The development of an Interpretable Therapeutic Peptide Prediction (ITP-Pred) model based on efficient feature fusion showed higher prediction performance in cross-validation and independent verification experiments, providing guidance for designing better models.

BRIEFINGS IN BIOINFORMATICS (2021)

Article Biochemical Research Methods

DeepYY1: a deep learning approach to identify YY1-mediated chromatin loops

Fu-Ying Dao et al.

Summary: YY1 protein forms dimers that enhance enhancer-promoter interactions, a general feature of mammalian gene control. A deep learning algorithm named DeepYY1 has been developed to efficiently identify YY1-mediated chromatin loops. Sequences play a crucial role in the formation of YY1-mediated chromatin loops.

BRIEFINGS IN BIOINFORMATICS (2021)

Article Biochemical Research Methods

Exploring associations of non-coding RNAs in human diseases via three-matrix factorization with hypergraph-regular terms on center kernel alignment

Hao Wang et al.

Summary: Exploring accurate associations between non-coding RNAs and diseases is crucial for human biomedical research, and new computational tools have been proposed to detect new associations based on known ncRNA and disease information. The novel computational method demonstrated excellent performance in the test and is able to discover new associations accurately between ncRNAs and diseases.

BRIEFINGS IN BIOINFORMATICS (2021)

Review Biotechnology & Applied Microbiology

Prediction of bio-sequence modifications and the associations with diseases

Chunyan Ao et al.

Summary: This review comprehensively summarizes the predictors for protein, RNA, and DNA modification sites and their association with diseases, emphasizing the importance of accurately identifying and understanding modification sites for disease research.

BRIEFINGS IN FUNCTIONAL GENOMICS (2021)

Article Mathematical & Computational Biology

Screening of Prospective Plant Compounds as H1R and CL1R Inhibitors and Its Antiallergic Efficacy through Molecular Docking Approach

Hasan Zulfiqar et al.

Summary: This research utilized molecular docking to identify the best inhibitors against H1R and CL1R, and evaluate their anti-allergic efficacy. This in silico study will aid in the design of novel, safe, and cost-effective drugs in the future to enhance the quality of human life.

COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE (2021)

Article Biochemistry & Molecular Biology

COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas

Xianwen Ren et al.

Summary: The study revealed the presence of immune response dysfunction in COVID-19 patients, with different peripheral immune subtype changes associated with clinical features such as age, sex, severity, and disease stages. Additionally, dramatic transcriptomic changes were observed within virus-infected cells, and upregulation of S100A8/A9 in peripheral blood may contribute to the cytokine storms frequently observed in severe patients.
Article Biotechnology & Applied Microbiology

Comprehensive analysis of TCR repertoire in COVID-19 using single cell sequencing

Pingping Wang et al.

Summary: This study analyzed the TCR repertoire in COVID-19 patients using single-cell V(D)J sequencing and found distinct T cell clonal expansion as well as significant changes in VJ gene combinations. Moreover, preferential usage of V and J gene segments was observed in samples infected by different viruses, providing novel insights on the immune response in COVID-19.

GENOMICS (2021)

Article Computer Science, Artificial Intelligence

Risk Prediction of Diabetes: Big data mining with fusion of multifarious physical examination indicators

Hui Yang et al.

Summary: The study designed a computational system to predict diabetes risk by combining various types of physical examination data. Statistical analysis was conducted on different physical examination indexes to develop a model that can distinguish diabetes patients from healthy individuals. A diabetes risk scorecard was established to improve the convenience and flexibility of the model. Lastly, an online diabetes risk assessment system was set up to enhance diabetes cascade screening and personal lifestyle management.

INFORMATION FUSION (2021)

Article Biochemical Research Methods

Predicting therapeutic drugs for hepatocellular carcinoma based on tissue-specific pathways

Liang Yu et al.

Summary: This study developed an effective method based on tissue-specific pathways to predict three potential therapeutic drugs for HCC. Experimental validation showed that two of these drugs significantly inhibited HCC cell viability, with one showing lower toxicity to normal cells. This suggests that the proposed approach is successful in discovering novel therapeutic options for HCC.

PLOS COMPUTATIONAL BIOLOGY (2021)

Review Biochemical Research Methods

TANTIGEN 2.0: a knowledge base of tumor T cell antigens and epitopes

Guanglan Zhang et al.

Summary: TANTIGEN 2.0 is a comprehensive database that catalogs thousands of antigen variants from over 400 unique tumor antigens, including T cell epitopes and neoantigens. It also offers a rich data resource and tailored data analytics tools for meaningful analysis workflows.

BMC BIOINFORMATICS (2021)

Article Computer Science, Artificial Intelligence

Prediction of drug-target interactions based on multi-layer network representation learning

Yifan Shang et al.

Summary: This study proposes a multilayer network representation learning method for drug-target interaction prediction, which integrates information from different networks, reduces noise, and learns feature vectors of drugs and targets to predict drug-target interactions.

NEUROCOMPUTING (2021)

Article Biochemical Research Methods

Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework

Leyi Wei et al.

Summary: The study introduced a novel machine learning approach called Stack-ORI to identify replication origin sites (ORIs) in four different eukaryotic species. Results showed that Stack-ORI outperformed baseline models on both training and independent datasets, consistently achieving better performance across all cell-specific models. The novel approach also provided necessary explanations for model success, highlighting the most important feature encoding schemes significant for predicting cell-specific ORIs.

BRIEFINGS IN BIOINFORMATICS (2021)

Article Computer Science, Artificial Intelligence

Comparison of SFS and mRMR for oximetry feature selection in obstructive sleep apnea detection

Sheikh Shanawaz Mostafa et al.

NEURAL COMPUTING & APPLICATIONS (2020)

Article Biochemical Research Methods

Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools

Ran Su et al.

BRIEFINGS IN BIOINFORMATICS (2020)

Article Biochemical Research Methods

ESDA: An Improved Approach to Accurately Identify Human snoRNAs for Precision Cancer Therapy

Yan-Mei Dong et al.

CURRENT BIOINFORMATICS (2020)

Article Biochemical Research Methods

Research on Gastric Cancer's Drug-resistant Gene Regulatory Network Model

Zhi Li et al.

CURRENT BIOINFORMATICS (2020)

Article Biochemical Research Methods

Predicting LncRNA Subcellular Localization Using Unbalanced Pseudo-k Nucleotide Compositions

Xiao-Fei Yang et al.

CURRENT BIOINFORMATICS (2020)

Review Biochemical Research Methods

Critical evaluation of web-based prediction tools for human protein subcellular localization

Yinan Shen et al.

BRIEFINGS IN BIOINFORMATICS (2020)

Article Computer Science, Artificial Intelligence

Identification of drug-target interactions via fuzzy bipartite local model

Yijie Ding et al.

NEURAL COMPUTING & APPLICATIONS (2020)

Article Biochemical Research Methods

iMRM: a platform for simultaneously identifying multiple kinds of RNA modifications

Kewei Liu et al.

BIOINFORMATICS (2020)

Article Biochemical Research Methods

Fold-LTR-TCP: protein fold recognition based on triadic closure principle

Bin Liu et al.

BRIEFINGS IN BIOINFORMATICS (2020)

Article Biochemical Research Methods

Citrullination Site Prediction by Incorporating Sequence Coupled Effects into PseAAC and Resolving Data Imbalance Issue

Md. Al Mehedi Hasan et al.

CURRENT BIOINFORMATICS (2020)

Article Biotechnology & Applied Microbiology

Predict New Therapeutic Drugs for Hepatocellular Carcinoma Based on Gene Mutation and Expression

Liang Yu et al.

FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY (2020)

Article Biochemical Research Methods

DeepLGP: a novel deep learning method for prioritizing lncRNA target genes

Tianyi Zhao et al.

BIOINFORMATICS (2020)

Review Biochemical Research Methods

A Review on the Methods of Peptide-MHC Binding Prediction

Yang Liu et al.

CURRENT BIOINFORMATICS (2020)

Article Biochemical Research Methods

iTTCA-Hybrid: Improved and robust identification of tumor T cell antigens by utilizing hybrid feature representation

Phasit Charoenkwan et al.

ANALYTICAL BIOCHEMISTRY (2020)

Article Biochemistry & Molecular Biology

Exploring Drug Treatment Patterns Based on the Action of Drug and Multilayer Network Model

Liang Yu et al.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2020)

Article Mathematical & Computational Biology

A Method for Identifying Vesicle Transport Proteins Based on LibSVM and MRMD

Zhiyu Tao et al.

COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE (2020)

Article Computer Science, Artificial Intelligence

Identification of Drug-Target Interactions via Dual Laplacian Regularized Least Squares with Multiple Kernel Fusion

Yijie Ding et al.

KNOWLEDGE-BASED SYSTEMS (2020)

Article Computer Science, Information Systems

DeepAVP: A Dual-Channel Deep Neural Network for Identifying Variable-Length Antiviral Peptides

Jiawei Li et al.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2020)

Article Biotechnology & Applied Microbiology

Prediction of antioxidant proteins using hybrid feature representation method and random forest

Chunyan Ao et al.

GENOMICS (2020)

Article Chemistry, Multidisciplinary

Target identification among known drugs by deep learning from heterogeneous networks

Xiangxiang Zeng et al.

CHEMICAL SCIENCE (2020)

Article Health Care Sciences & Services

Transformed low-rank ANOVA models for high-dimensional variable selection

Yoonsuh Jung et al.

STATISTICAL METHODS IN MEDICAL RESEARCH (2019)

Article Biochemical Research Methods

PyFeat: a Python-based effective feature generation tool for DNA, RNA and protein sequences

Rafsanjani Muhammod et al.

BIOINFORMATICS (2019)

Article Biochemical Research Methods

Predicting Drug Side Effects with Compact Integration of Heterogeneous Networks

Xian Zhao et al.

CURRENT BIOINFORMATICS (2019)

Article Biochemical Research Methods

ELM-MHC: An Improved MHC Identification Method with Extreme Learning Machine Algorithm

Yanjuan Li et al.

JOURNAL OF PROTEOME RESEARCH (2019)

Article Biochemical Research Methods

deepDR: a network-based deep learning approach to in silico drug repositioning

Xiangxiang Zeng et al.

BIOINFORMATICS (2019)

Article Computer Science, Artificial Intelligence

DUNet: A deformable network for retinal vessel segmentation

Qiangguo Jin et al.

KNOWLEDGE-BASED SYSTEMS (2019)

Article Automation & Control Systems

iLys-Khib: Identify lysine 2-Hydroxyisobutyrylation sites using mRMR feature selection and fuzzy SVM algorithm

Zhe Ju et al.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2019)

Review Genetics & Heredity

Gene-based Therapeutic Tools in the Treatment of Cornea Disease

Xiao-Xiao Lu et al.

CURRENT GENE THERAPY (2019)

Article Biology

TTAgP 1.0: A computational tool for the specific prediction of tumor T cell antigens

Jorge Felix Beltran Lissabet et al.

COMPUTATIONAL BIOLOGY AND CHEMISTRY (2019)

Article Computer Science, Artificial Intelligence

Identification of drug-side effect association via multiple information integration with centered kernel alignment

Yijie Ding et al.

NEUROCOMPUTING (2019)

Article Biochemistry & Molecular Biology

The Immune Epitope Database (IEDB): 2018 update

Randi Vita et al.

NUCLEIC ACIDS RESEARCH (2019)

Article Biochemical Research Methods

MetSigDis: a manually curated resource for the metabolic signatures of diseases

Liang Cheng et al.

BRIEFINGS IN BIOINFORMATICS (2019)

Article Mathematical & Computational Biology

Identification of hormone binding proteins based on machine learning methods

Jiu-Xin Tan et al.

MATHEMATICAL BIOSCIENCES AND ENGINEERING (2019)

Article Biochemistry & Molecular Biology

RMBase v2.0: deciphering the map of RNA modifications from epitranscriptome sequencing data

Jia-Jia Xuan et al.

NUCLEIC ACIDS RESEARCH (2018)

Review Oncology

Emerging targets in cancer immunotherapy

Samantha Burugu et al.

SEMINARS IN CANCER BIOLOGY (2018)

Article Biochemical Research Methods

Prediction of potential disease-associated microRNAs using structural perturbation method

Xiangxiang Zeng et al.

BIOINFORMATICS (2018)

Article Medicine, Research & Experimental

M6APred-EL: A Sequence-Based Predictor for Identifying N6-methyladenosine Sites Using Ensemble Learning

Leyi Wei et al.

MOLECULAR THERAPY-NUCLEIC ACIDS (2018)

Article Biochemical Research Methods

Prediction and Validation of Disease Genes Using HeteSim Scores

Xiangxiang Zeng et al.

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2017)

Article Computer Science, Information Systems

Identification of drug-target interactions via multiple information integration

Yijie Ding et al.

INFORMATION SCIENCES (2017)

Review Biochemical Research Methods

A comprehensive overview and evaluation of circular RNA detection tools

Xiangxiang Zeng et al.

PLOS COMPUTATIONAL BIOLOGY (2017)

Article Computer Science, Artificial Intelligence

Improved prediction of protein-protein interactions using novel negative samples, features, and an ensemble classifier

Leyi Wei et al.

ARTIFICIAL INTELLIGENCE IN MEDICINE (2017)

Article Computer Science, Artificial Intelligence

A novel hierarchical selective ensemble classifier with bioinformatics application

Leyi Wei et al.

ARTIFICIAL INTELLIGENCE IN MEDICINE (2017)

Article Oncology

TANTIGEN: a comprehensive database of tumor T cell antigens

Lars Ronn Olsen et al.

CANCER IMMUNOLOGY IMMUNOTHERAPY (2017)

Article Computer Science, Theory & Methods

A Survey of Predictive Modeling on Im balanced Domains

Paula Branco et al.

ACM COMPUTING SURVEYS (2016)

Article Biochemistry & Molecular Biology

Identification of immunoglobulins using Chou's pseudo amino acid composition with feature selection technique

Hua Tang et al.

MOLECULAR BIOSYSTEMS (2016)

Article Computer Science, Artificial Intelligence

A novel features ranking metric with application to scalable visual and bioinformatics data classification

Quan Zou et al.

NEUROCOMPUTING (2016)

Article Computer Science, Artificial Intelligence

Finding the Best Classification Threshold in Imbalanced Classification

Quan Zou et al.

BIG DATA RESEARCH (2016)

Article Biochemical Research Methods

Improved and Promising Identification of Human MicroRNAs by Incorporating a High-Quality Negative Set

Leyi Wei et al.

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2014)

Article Mathematical & Computational Biology

Computational systems biology in the big data era

Yong Wang et al.

BMC SYSTEMS BIOLOGY (2013)

Article Mathematical & Computational Biology

Predicting human microRNA-disease associations based on support vector machine

Qinghua Jiang et al.

INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS (2013)

News Item Multidisciplinary Sciences

Cancer Immunotherapy

Jennifer Couzin-Frankel

SCIENCE (2013)

Article Biotechnology & Applied Microbiology

An Approach for Identifying Cytokines Based on a Novel Ensemble Classifier

Quan Zou et al.

BIOMED RESEARCH INTERNATIONAL (2013)

Review Oncology

Trial Watch Peptide vaccines in cancer therapy

Fernando Aranda et al.

ONCOIMMUNOLOGY (2013)

Review Biology

Some remarks on protein attribute prediction and pseudo amino acid composition

Kuo-Chen Chou

JOURNAL OF THEORETICAL BIOLOGY (2011)

Article Biochemical Research Methods

Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes

KC Chou

BIOINFORMATICS (2005)