Carl Kingsford

Molecular Biology · 2007–2019

A researcher in the Science corpus: 7 papers; trusts 24 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 64 citations into it; #1,915 of 17,773 by trust here, #3,835 by citations
• Cancer Research — 9 citations into it; #1,206 of 1,780 by trust here, #823 by citations
• Artificial Intelligence — 8 citations into it; #10,355 of 35,345 by trust here, #16,166 by citations
• Genetics — 7 citations into it; #709 of 6,854 by trust here, #2,123 by citations
• Computational Biology & Bioinformatics — 5 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it
• Plant Science — 5 citations into it

Whom Carl Kingsford trusts overall

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

1. David John Cameron MacKay
2. Muthu Dayalan
3. Robert C. Edgar
4. Michael C. Schatz
5. Steven L. Salzberg
6. Robert E. Schapire
7. Adam Roberts
8. David R. Kelley
9. J. Chen
10. Sebastian Köhler

Who trusts Carl Kingsford overall

1. Geoffrey L. Winsor
2. Li Song
3. Derrick E. Wood
4. Steven L. Salzberg
5. Francesca Nadalin
6. Susan Dina Ghiassian
7. Daehwan Kim
8. Alaina Shumate
9. Jie Jessie Ren
10. Peter Csermely

Papers from Carl Kingsford's perspective

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

1. Information Theory, Inference, and Learning Algorithms
2. Mapping and quantifying mammalian transcriptomes by RNA-Seq (Nature Methods)
3. Pattern Recognition and Machine Learning
4. Spontaneous mapping of number and space in adults and young children (Cognition)
5. Improving RNA-Seq expression estimates by correcting for fragment bias (Genome Biology)
6. Fast gapped-read alignment with Bowtie 2
7. MUSCLE: multiple sequence alignment with high accuracy and high throughput.
8. A whole-genome assembly of Drosophila. (Science)
9. Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers
10. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers (Bioinform.)

Their papers

• Salmon: fast and bias-aware quantification of transcript expression using dual-phase inference (2017) — 8,742 citations
• A fast, lock-free approach for efficient parallel counting of occurrences of k-mers (2011) — 4,185 citations
• Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms (2013) — 632 citations
• The power of protein interaction networks for associating genes with diseases (2010) — 379 citations
• Rapid, accurate, computational discovery of Rho-independent transcription terminators illuminates their relationship to DNA uptake (2007) — 518 citations
• The human body at cellular resolution: the NIH Human Biomolecular Atlas Program (2019) — 537 citations
• What are decision trees? (2008) — 443 citations