These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

106 related articles for article (PubMed ID: 36370584)

  • 1. Repulsion and attraction in searching: A hybrid algorithm based on gravitational kernel and vital few for cancer driver gene prediction.
    He Z; Lin Y; Wei R; Liu C; Jiang D
    Comput Biol Med; 2022 Dec; 151(Pt A):106236. PubMed ID: 36370584
    [TBL] [Abstract][Full Text] [Related]  

  • 2. LOTUS: A single- and multitask machine learning algorithm for the prediction of cancer driver genes.
    Collier O; Stoven V; Vert JP
    PLoS Comput Biol; 2019 Sep; 15(9):e1007381. PubMed ID: 31568528
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine Learning Classification and Structure-Functional Analysis of Cancer Mutations Reveal Unique Dynamic and Network Signatures of Driver Sites in Oncogenes and Tumor Suppressor Genes.
    Agajanian S; Odeyemi O; Bischoff N; Ratra S; Verkhivker GM
    J Chem Inf Model; 2018 Oct; 58(10):2131-2150. PubMed ID: 30253099
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Effects of Multi-Omics Characteristics on Identification of Driver Genes Using Machine Learning Algorithms.
    Li F; Chu X; Dai L; Wang J; Liu J; Shang J
    Genes (Basel); 2022 Apr; 13(5):. PubMed ID: 35627101
    [TBL] [Abstract][Full Text] [Related]  

  • 5. DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies.
    Han Y; Yang J; Qian X; Cheng WC; Liu SH; Hua X; Zhou L; Yang Y; Wu Q; Liu P; Lu Y
    Nucleic Acids Res; 2019 May; 47(8):e45. PubMed ID: 30773592
    [TBL] [Abstract][Full Text] [Related]  

  • 6. LRT-CLUSTER: A New Clustering Algorithm Based on Likelihood Ratio Test to Identify Driving Genes.
    Quan C; Liu F; Qi L; Tie Y
    Interdiscip Sci; 2023 Jun; 15(2):217-230. PubMed ID: 36848004
    [TBL] [Abstract][Full Text] [Related]  

  • 7. EPIMUTESTR: a nearest neighbor machine learning approach to predict cancer driver genes from the evolutionary action of coding variants.
    Parvandeh S; Donehower LA; Panagiotis K; Hsu TK; Asmussen JK; Lee K; Lichtarge O
    Nucleic Acids Res; 2022 Jul; 50(12):e70. PubMed ID: 35412634
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Network embedding framework for driver gene discovery by combining functional and structural information.
    Chu X; Guan B; Dai L; Liu JX; Li F; Shang J
    BMC Genomics; 2023 Jul; 24(1):426. PubMed ID: 37516822
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Synstable Fusion: A Network-Based Algorithm for Estimating Driver Genes in Fusion Structures.
    Xu M; Zhao Z; Zhang X; Gao A; Wu S; Wang J
    Molecules; 2018 Aug; 23(8):. PubMed ID: 30115851
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Comprehensive evaluation of computational methods for predicting cancer driver genes.
    Shi X; Teng H; Shi L; Bi W; Wei W; Mao F; Sun Z
    Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35037014
    [TBL] [Abstract][Full Text] [Related]  

  • 11. PrognosiT: Pathway/gene set-based tumour volume prediction using multiple kernel learning.
    Bektaş AB; Gönen M
    BMC Bioinformatics; 2021 Nov; 22(1):537. PubMed ID: 34727887
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Temperature drift compensation of a FOG based on an HKSVM optimized by an improved hybrid BAS-GSA algorithm.
    Liu J; Chen X
    Appl Opt; 2021 Dec; 60(34):10539-10547. PubMed ID: 35200914
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Evaluating machine learning methodologies for identification of cancer driver genes.
    Malebary SJ; Khan YD
    Sci Rep; 2021 Jun; 11(1):12281. PubMed ID: 34112883
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Enhancing Cancer Driver Gene Prediction by Protein-Protein Interaction Network.
    Liu C; Dai Y; Yu K; Zhang ZK
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(4):2231-2240. PubMed ID: 33656997
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Gene gravity-like algorithm for disease gene prediction based on phenotype-specific network.
    Lin L; Yang T; Fang L; Yang J; Yang F; Zhao J
    BMC Syst Biol; 2017 Dec; 11(1):121. PubMed ID: 29212543
    [TBL] [Abstract][Full Text] [Related]  

  • 16. InDEP: an interpretable machine learning approach to predict cancer driver genes from multi-omics data.
    Yang H; Liu Y; Yang Y; Li D; Wang Z
    Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37649392
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A new hybrid prediction model of air quality index based on secondary decomposition and improved kernel extreme learning machine.
    Li G; Tang Y; Yang H
    Chemosphere; 2022 Oct; 305():135348. PubMed ID: 35718028
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Random Global and Local Optimal Search Algorithm Based Subset Generation for Diagnosis of Cancer.
    Meenachi L; Ramakrishnan S
    Curr Med Imaging; 2020; 16(3):249-261. PubMed ID: 32133955
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Machine learning optimized DriverDetect software for high precision prediction of deleterious mutations in human cancers.
    Koh HYK; Lam UTF; Ban KH; Chen ES
    Sci Rep; 2024 Sep; 14(1):22618. PubMed ID: 39349509
    [TBL] [Abstract][Full Text] [Related]  

  • 20. DriverRWH: discovering cancer driver genes by random walk on a gene mutation hypergraph.
    Wang C; Shi J; Cai J; Zhang Y; Zheng X; Zhang N
    BMC Bioinformatics; 2022 Jul; 23(1):277. PubMed ID: 35831792
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.