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Infer related genes from large scale gene expression dataset with embedding
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1016/j.biosystems.2017.09.017openalex-snapshot
Incorporating gene ontology into fuzzy relational clustering of microarray gene expression data
inferredcites →https://doi.org/10.1016/j.cell.2017.05.046openalex-snapshot
Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma
inferredcites →https://doi.org/10.1016/j.csbj.2018.01.001openalex-snapshot
Machine Learning Methods for Histopathological Image Analysis
inferredcites →https://doi.org/10.1016/j.ebiom.2017.12.026openalex-snapshot
Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images
inferredcites →https://doi.org/10.1016/j.fcij.2017.12.001openalex-snapshot
Classification using deep learning neural networks for brain tumors
inferredcites →https://doi.org/10.1021/acs.molpharmaceut.6b00248openalex-snapshot
Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data
inferredcites →https://doi.org/10.1038/nature16961openalex-snapshot
Mastering the game of Go with deep neural networks and tree search
inferredcites →https://doi.org/10.1038/nbt.2463openalex-snapshot
A gene ontology inferred from molecular networks
inferredcites →https://doi.org/10.1038/nmeth.4627openalex-snapshot
Using deep learning to model the hierarchical structure and function of a cell
inferredcites →https://doi.org/10.1038/s41598-017-04075-zopenalex-snapshot
Breast Cancer Multi-classification from Histopathological Images with Structured Deep Learning Model
inferredcites →https://doi.org/10.1038/s41598-018-22437-zopenalex-snapshot
Detecting and classifying lesions in mammograms with Deep Learning
inferredcites →https://doi.org/10.1038/srep26286openalex-snapshot
Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis
inferredcites →https://doi.org/10.1038/srep39237openalex-snapshot
Integrating Information in Biological Ontologies and Molecular Networks to Infer Novel Terms
inferredcites →https://doi.org/10.1093/bioinformatics/bts405openalex-snapshot
Bayesian assignment of gene ontology terms to gene expression experiments
inferredcites →https://doi.org/10.1093/bioinformatics/btu282openalex-snapshot
Inferring gene ontologies from pairwise similarity data
inferredcites →https://doi.org/10.1093/bioinformatics/btw344openalex-snapshot
Evaluating the molecule-based prediction of clinical drug responses in cancer
inferredcites →https://doi.org/10.1093/bioinformatics/btx806openalex-snapshot
DeepSynergy: predicting anti-cancer drug synergy with Deep Learning
inferredcites →https://doi.org/10.1093/nar/gkw1108openalex-snapshot
Expansion of the Gene Ontology knowledgebase and resources
inferredcites →https://doi.org/10.1101/070490openalex-snapshot
Deep Learning and Association Rule Mining for Predicting Drug Response in Cancer. A Personalised Medicine Approach
inferredcites →https://doi.org/10.1101/278739openalex-snapshot
DeepProfile: Deep learning of cancer molecular profiles for precision medicine
inferredcites →https://doi.org/10.1109/icassp.2013.6639347openalex-snapshot
Deep convolutional neural networks for LVCSR
inferredcites →https://doi.org/10.1142/9789813235533_0008openalex-snapshot
Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1155/2009/356120openalex-snapshot
A General Rate K/N Convolutional Decoder Based on Neural Networks with Stopping Criterion
inferredcites →https://doi.org/10.1155/2009/421425openalex-snapshot
A Survey of Collaborative Filtering Techniques
inferredcites →https://doi.org/10.1186/s12859-016-1250-zopenalex-snapshot
GeneSCF: a real-time based functional enrichment tool with support for multiple organisms
inferredcites →https://doi.org/10.1371/journal.pone.0013984openalex-snapshot
Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation
inferredcites →https://doi.org/10.1371/journal.pone.0061318openalex-snapshot
Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties
inferredcites →https://doi.org/10.1371/journal.pone.0141287openalex-snapshot
Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics
inferredcites →https://doi.org/10.1371/journal.pone.0177544openalex-snapshot
Classification of breast cancer histology images using Convolutional Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1301.3781openalex-snapshot
Efficient Estimation of Word Representations in Vector Space
inferredcites →https://doi.org/10.48550/arxiv.1310.4546openalex-snapshot
Distributed Representations of Words and Phrases and their Compositionality
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-1-0716-4662-5_14openalex-snapshot
A Benchmarking Platform for Assessing Protein Language Models on Function-Related Prediction Tasks
inferred← citeshttps://doi.org/10.1038/s42256-022-00457-9openalex-snapshot
Learning functional properties of proteins with language models
inferred← citeshttps://doi.org/10.1101/2020.10.28.359828openalex-snapshot
Evaluation of Methods for Protein Representation Learning: A Quantitative Analysis
inferred← citeshttps://doi.org/10.1101/2023.08.23.554486openalex-snapshot
Domain-PFP: Protein Function Prediction Using Function-Aware Domain Embedding Representations
inferred← citeshttps://doi.org/10.1101/2025.01.29.635607openalex-snapshot
Benchmarking gene embeddings from sequence, expression, network, and text models for functional prediction tasks
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