Dokyoon Kim

Nature reviews genetics · 2015–2019

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Dokyoon Kim trusts

Their strongest outbound trust, strongest first, inferred from their citations.

1. David Ruppert (in Evaluation & Benchmarks)

Papers from Dokyoon Kim's perspective

Ordered by how strongly the researchers Dokyoon Kim trusts endorse each paper. Same corpus, a different order for every researcher.

1. Unsupervised Learning of Video Representations using LSTMs
2. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
3. Principal components analysis corrects for stratification in genome-wide association studies
4. The case for cloud computing in genome informatics
5. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. (Genome Research)
6. Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions
7. An integrative genomics approach to infer causal associations between gene expression and disease (Nature Genetics)
8. Sparse Principal Component Analysis
9. Transcriptome and genome sequencing uncovers functional variation in humans (Nature)
10. Quality Control Procedures for Genome Wide Association Studies (Current Protocols in Human Genetics)

Their papers

• Methods of integrating data to uncover genotype–phenotype interactions (2015) — 983 citations
• Predicting Alzheimer’s disease progression using multi-modal deep learning approach (2019) — 385 citations
• Continuous O2-Evolving MnFe2O4 Nanoparticle-Anchored Mesoporous Silica Nanoparticles for Efficient Photodynamic Therapy in Hypoxic Cancer. (2017) — 608 citations