Emma Laks

5.1k total citations · 1 hit paper
7 papers, 960 citations indexed

About

Emma Laks is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Emma Laks has authored 7 papers receiving a total of 960 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Cancer Research and 2 papers in Genetics. Recurrent topics in Emma Laks's work include Single-cell and spatial transcriptomics (7 papers), Cancer Genomics and Diagnostics (6 papers) and Epigenetics and DNA Methylation (2 papers). Emma Laks is often cited by papers focused on Single-cell and spatial transcriptomics (7 papers), Cancer Genomics and Diagnostics (6 papers) and Epigenetics and DNA Methylation (2 papers). Emma Laks collaborates with scholars based in Canada and United States. Emma Laks's co-authors include Samuel Aparício, Sohrab P. Shah, Justina Biele, Alexandre Bouchard‐Côté, Damian Yap, Adrian Wan, Andrew Roth, Gavin Ha, Jaswinder Khattra and Adi Steif and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Methods and Genome biology.

In The Last Decade

Emma Laks

7 papers receiving 951 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

PyClone: statistical inference of clonal population structure in cancer

2014 575 citations Andrew Roth, Jaswinder Khattra et al. Nature Methods profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Emma Laks Canada	7	670	625	257	167	132	7	960
Justina Biele Canada	6	558 0.8×	473 0.8×	222 0.9×	162 1.0×	104 0.8×	6	781
Anna K. Unruh United States	6	651 1.0×	565 0.9×	282 1.1×	109 0.7×	120 0.9×	8	896
Ruping Sun United States	12	619 0.9×	613 1.0×	257 1.0×	122 0.7×	172 1.3×	20	1.1k
Xiuqing Shi China	6	875 1.3×	732 1.2×	469 1.8×	156 0.9×	189 1.4×	9	1.2k
Marco L. Leung United States	7	948 1.4×	939 1.5×	499 1.9×	151 0.9×	222 1.7×	21	1.4k
Alexander Davis United States	8	746 1.1×	795 1.3×	376 1.5×	122 0.7×	160 1.2×	10	1.2k
Bryce P. Portier United States	19	401 0.6×	715 1.1×	497 1.9×	177 1.1×	74 0.6×	37	1.3k
Henry Lee-Six United Kingdom	8	534 0.8×	566 0.9×	362 1.4×	185 1.1×	171 1.3×	14	1.1k
Inga Hansine Rye Norway	9	606 0.9×	628 1.0×	330 1.3×	144 0.9×	226 1.7×	13	1.1k
Junsong Zhao United States	6	513 0.8×	291 0.5×	318 1.2×	225 1.3×	156 1.2×	8	746

Countries citing papers authored by Emma Laks

Since Specialization

Citations

This map shows the geographic impact of Emma Laks's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Emma Laks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emma Laks more than expected).

Fields of papers citing papers by Emma Laks

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emma Laks. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Emma Laks. The network helps show where Emma Laks may publish in the future.

Co-authorship network of co-authors of Emma Laks

This figure shows the co-authorship network connecting the top 25 collaborators of Emma Laks. A scholar is included among the top collaborators of Emma Laks based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Emma Laks. Emma Laks is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Souza, Camila P. E. de, Mirela Andronescu, Tehmina Masud, et al.. (2020). Epiclomal: Probabilistic clustering of sparse single-cell DNA methylation data. PLoS Computational Biology. 16(9). e1008270–e1008270. 15 indexed citations

2.

Campbell, Kieran R., Adi Steif, Emma Laks, et al.. (2019). clonealign: statistical integration of independent single-cell RNA and DNA sequencing data from human cancers. Genome biology. 20(1). 54–54. 69 indexed citations

3.

Cao, Qi, Kieran O’Neill, Colin A. Hammond, et al.. (2018). High-Resolution Single-Cell DNA Methylation Measurements Reveal Epigenetically Distinct Hematopoietic Stem Cell Subpopulations. Stem Cell Reports. 11(2). 578–592. 62 indexed citations

4.

Zahn, Hans, Adi Steif, Emma Laks, et al.. (2017). Scalable whole-genome single-cell library preparation without preamplification. Nature Methods. 14(2). 167–173. 130 indexed citations

5.

Roth, Andrew, Andrew McPherson, Emma Laks, et al.. (2016). Clonal genotype and population structure inference from single-cell tumor sequencing. Nature Methods. 13(7). 573–576. 75 indexed citations

6.

Leung, Kaston, Emma Laks, Justina Biele, et al.. (2016). Robust high-performance nanoliter-volume single-cell multiple displacement amplification on planar substrates. Proceedings of the National Academy of Sciences. 113(30). 8484–8489. 34 indexed citations

7.

Roth, Andrew, Jaswinder Khattra, Damian Yap, et al.. (2014). PyClone: statistical inference of clonal population structure in cancer. Nature Methods. 11(4). 396–398. 575 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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