Saved in:
| Main Authors: | Si, Weichen, Ou, Yihao, Tian, Zhen |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.19740 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
GastroDL-Fusion: A Dual-Modal Deep Learning Framework Integrating Protein-Ligand Complexes and Gene Sequences for Gastrointestinal Disease Drug Discovery
by: Gao, Ziyang, et al.
Published: (2025)
by: Gao, Ziyang, et al.
Published: (2025)
Machine Learning-Based Genomic Linguistic Analysis (Gene Sequence Feature Learning): A Case Study on Predicting Heavy Metal Response Genes in Rice
by: Yang, Ruiqi, et al.
Published: (2025)
by: Yang, Ruiqi, et al.
Published: (2025)
GenePheno: Interpretable Gene Knockout-Induced Phenotype Abnormality Prediction from Gene Sequences
by: Yan, Jingquan, et al.
Published: (2025)
by: Yan, Jingquan, et al.
Published: (2025)
Predicting Gene Disease Associations in Type 2 Diabetes Using Machine Learning on Single-Cell RNA-Seq Data
by: Toledo, Maria De La Luz Lomboy, et al.
Published: (2026)
by: Toledo, Maria De La Luz Lomboy, et al.
Published: (2026)
DNAZEN: Enhanced Gene Sequence Representations via Mixed Granularities of Coding Units
by: Mao, Lei, et al.
Published: (2025)
by: Mao, Lei, et al.
Published: (2025)
Machine Learning Methods for Gene Regulatory Network Inference
by: Hegde, Akshata, et al.
Published: (2025)
by: Hegde, Akshata, et al.
Published: (2025)
Machine Learning for Quantum Noise Reduction
by: Kendre, Karan
Published: (2025)
by: Kendre, Karan
Published: (2025)
Feature-Enhanced Machine Learning for All-Cause Mortality Prediction in Healthcare Data
by: Lee, HyeYoung, et al.
Published: (2025)
by: Lee, HyeYoung, et al.
Published: (2025)
Generative Language Models on Nucleotide Sequences of Human Genes
by: Ihtiyar, Musa Nuri, et al.
Published: (2023)
by: Ihtiyar, Musa Nuri, et al.
Published: (2023)
An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction
by: Liang, Yaxin, et al.
Published: (2024)
by: Liang, Yaxin, et al.
Published: (2024)
Auxiliary Gene Learning: Spatial Gene Expression Estimation by Auxiliary Gene Selection
by: Shiku, Kaito, et al.
Published: (2025)
by: Shiku, Kaito, et al.
Published: (2025)
Machine Learning-Based Differential Diagnosis of Parkinson's Disease Using Kinematic Feature Extraction and Selection
by: Matsumoto, Masahiro, et al.
Published: (2025)
by: Matsumoto, Masahiro, et al.
Published: (2025)
Beyond Independent Genes: Learning Module-Inductive Representations for Gene Perturbation Prediction
by: Ruan, Jiafa, et al.
Published: (2026)
by: Ruan, Jiafa, et al.
Published: (2026)
BSM: Small but Powerful Biological Sequence Model for Genes and Proteins
by: Xiang, Weixi, et al.
Published: (2024)
by: Xiang, Weixi, et al.
Published: (2024)
Gradient Boosting Mapping for Dimensionality Reduction and Feature Extraction
by: Patron, Anri, et al.
Published: (2024)
by: Patron, Anri, et al.
Published: (2024)
A Comparative Analysis of Gene Expression Profiling by Statistical and Machine Learning Approaches
by: Bontonou, Myriam, et al.
Published: (2024)
by: Bontonou, Myriam, et al.
Published: (2024)
Refinement Contrastive Learning of Cell-Gene Associations for Unsupervised Cell Type Identification
by: Peng, Liang, et al.
Published: (2025)
by: Peng, Liang, et al.
Published: (2025)
Machine Learning-Based Analysis of Ebola Virus' Impact on Gene Expression in Nonhuman Primates
by: Rezapour, Mostafa, et al.
Published: (2024)
by: Rezapour, Mostafa, et al.
Published: (2024)
Utilizing Machine Learning for Signal Classification and Noise Reduction in Amateur Radio
by: Sanchez, Jimi
Published: (2024)
by: Sanchez, Jimi
Published: (2024)
Multimodal Representation Learning using Adaptive Graph Construction
by: Huang, Weichen
Published: (2024)
by: Huang, Weichen
Published: (2024)
Enhancing Noise Robustness of Parkinson's Disease Telemonitoring via Contrastive Feature Augmentation
by: Tang, Ziming, et al.
Published: (2025)
by: Tang, Ziming, et al.
Published: (2025)
Adversarial Imitation Learning with General Function Approximation: Theoretical Analysis and Practical Algorithms
by: Xu, Tian, et al.
Published: (2026)
by: Xu, Tian, et al.
Published: (2026)
A Contrast Based Feature Selection Algorithm for High-dimensional Data set in Machine Learning
by: Cao, Chunxu, et al.
Published: (2024)
by: Cao, Chunxu, et al.
Published: (2024)
Unravelling Causal Genetic Biomarkers of Alzheimer's Disease via Neuron to Gene-token Backtracking in Neural Architecture: A Groundbreaking Reverse-Gene-Finder Approach
by: Li, Victor OK, et al.
Published: (2025)
by: Li, Victor OK, et al.
Published: (2025)
Supervised Graph Contrastive Learning for Gene Regulatory Networks
by: Oshima, Sho, et al.
Published: (2025)
by: Oshima, Sho, et al.
Published: (2025)
Dive into Machine Learning Algorithms for Influenza Virus Host Prediction with Hemagglutinin Sequences
by: Xu, Yanhua, et al.
Published: (2022)
by: Xu, Yanhua, et al.
Published: (2022)
GoBERT: Gene Ontology Graph Informed BERT for Universal Gene Function Prediction
by: Miao, Yuwei, et al.
Published: (2025)
by: Miao, Yuwei, et al.
Published: (2025)
Feature Dimensionality Outweighs Model Complexity in Breast Cancer Subtype Classification Using TCGA-BRCA Gene Expression Data
by: Hasani, Meena Al
Published: (2026)
by: Hasani, Meena Al
Published: (2026)
Comparative Study of Machine Learning Algorithms in Detecting Cardiovascular Diseases
by: K, Dayana, et al.
Published: (2024)
by: K, Dayana, et al.
Published: (2024)
Classification and Prediction of Heart Diseases using Machine Learning Algorithms
by: Osei-Nkwantabisa, Akua Sekyiwaa, et al.
Published: (2024)
by: Osei-Nkwantabisa, Akua Sekyiwaa, et al.
Published: (2024)
Reduction-based Pseudo-label Generation for Instance-dependent Partial Label Learning
by: Qiao, Congyu, et al.
Published: (2024)
by: Qiao, Congyu, et al.
Published: (2024)
Graph Attention Based Prioritization of Disease Responsible Genes from Multimodal Alzheimer's Network
by: Teji, Binon, et al.
Published: (2026)
by: Teji, Binon, et al.
Published: (2026)
Heterogeneous Causal Metapath Graph Neural Network for Gene-Microbe-Disease Association Prediction
by: Zhang, Kexin, et al.
Published: (2024)
by: Zhang, Kexin, et al.
Published: (2024)
On the Recoverability of Causal Relations from Bulk Gene Expression Data
by: Luo, Gongxu, et al.
Published: (2026)
by: Luo, Gongxu, et al.
Published: (2026)
LCEN: A Nonlinear, Interpretable Feature Selection and Machine Learning Algorithm
by: Seber, Pedro, et al.
Published: (2024)
by: Seber, Pedro, et al.
Published: (2024)
Extending Sequence Length is Not All You Need: Effective Integration of Multimodal Signals for Gene Expression Prediction
by: Yang, Zhao, et al.
Published: (2026)
by: Yang, Zhao, et al.
Published: (2026)
Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise
by: Xue, Yihao, et al.
Published: (2022)
by: Xue, Yihao, et al.
Published: (2022)
Boundary-Guided Learning for Gene Expression Prediction in Spatial Transcriptomics
by: Qu, Mingcheng, et al.
Published: (2024)
by: Qu, Mingcheng, et al.
Published: (2024)
Feature Selection via Robust Weighted Score for High Dimensional Binary Class-Imbalanced Gene Expression Data
by: Khan, Zardad, et al.
Published: (2024)
by: Khan, Zardad, et al.
Published: (2024)
Prediction by Machine Learning Analysis of Genomic Data Phenotypic Frost Tolerance in Perccottus glenii
by: Fan, Lilin, et al.
Published: (2024)
by: Fan, Lilin, et al.
Published: (2024)
Similar Items
-
GastroDL-Fusion: A Dual-Modal Deep Learning Framework Integrating Protein-Ligand Complexes and Gene Sequences for Gastrointestinal Disease Drug Discovery
by: Gao, Ziyang, et al.
Published: (2025) -
Machine Learning-Based Genomic Linguistic Analysis (Gene Sequence Feature Learning): A Case Study on Predicting Heavy Metal Response Genes in Rice
by: Yang, Ruiqi, et al.
Published: (2025) -
GenePheno: Interpretable Gene Knockout-Induced Phenotype Abnormality Prediction from Gene Sequences
by: Yan, Jingquan, et al.
Published: (2025) -
Predicting Gene Disease Associations in Type 2 Diabetes Using Machine Learning on Single-Cell RNA-Seq Data
by: Toledo, Maria De La Luz Lomboy, et al.
Published: (2026) -
DNAZEN: Enhanced Gene Sequence Representations via Mixed Granularities of Coding Units
by: Mao, Lei, et al.
Published: (2025)