David H. Alexander

Molecular Biology · with Chang · 2016–2018

A researcher in the Science corpus: 3 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 53 citations into it
• Artificial Intelligence — 19 citations into it
• Model Architectures — 7 citations into it

Whom David H. Alexander trusts overall

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

1. Heng Li

Papers from David H. Alexander's perspective

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

1. Dropout: a simple way to prevent neural networks from overfitting
2. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
3. Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
4. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM
5. Rectifier Nonlinearities Improve Neural Network Acoustic Models
6. Basic local alignment search tool.
7. BLAST+: architecture and applications
8. Kraken: ultrafast metagenomic sequence classification using exact alignments (Genome Biology)
9. The Ribosomal Database Project (RDP-II): sequences and tools for high-throughput rRNA analysis (Nucleic Acids Res.)
10. Fast and accurate long-read alignment with Burrows–Wheeler transform (Bioinform.)

Their papers

• Creating a universal SNP and small indel variant caller with deep neural networks (2016) — 103 citations
• A deep learning approach to pattern recognition for short DNA sequences (2018) — 59 citations
• A universal SNP and small-indel variant caller using deep neural networks (2018) — 1,463 citations