Sara Ballouz

1.9k total citations
28 papers, 984 citations indexed

About

Sara Ballouz is a scholar working on Molecular Biology, Genetics and Genetics. According to data from OpenAlex, Sara Ballouz has authored 28 papers receiving a total of 984 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 11 papers in Genetics and 1 paper in Genetics. Recurrent topics in Sara Ballouz's work include Bioinformatics and Genomic Networks (18 papers), Single-cell and spatial transcriptomics (7 papers) and Gene expression and cancer classification (7 papers). Sara Ballouz is often cited by papers focused on Bioinformatics and Genomic Networks (18 papers), Single-cell and spatial transcriptomics (7 papers) and Gene expression and cancer classification (7 papers). Sara Ballouz collaborates with scholars based in United States, Australia and Canada. Sara Ballouz's co-authors include Jesse Gillis, Megan Crow, Paul Pavlidis, Alexander Dobin, Anirban Paul, Zhi Huang, Merridee A. Wouters, Nathaniel C. Lim, Melanie Weber and Andrew Francis and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Sara Ballouz

28 papers receiving 975 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sara Ballouz United States 16 788 186 80 79 71 28 984
George C. Tseng United States 10 887 1.1× 237 1.3× 67 0.8× 124 1.6× 29 0.4× 12 1.2k
Juan A. G. Ranea Spain 20 1.1k 1.3× 197 1.1× 86 1.1× 44 0.6× 85 1.2× 73 1.4k
Robin Haw Canada 17 1.2k 1.5× 111 0.6× 194 2.4× 101 1.3× 68 1.0× 27 1.5k
Sergei Egorov United States 5 699 0.9× 95 0.5× 66 0.8× 76 1.0× 94 1.3× 5 949
Guan Ning Lin China 17 944 1.2× 433 2.3× 133 1.7× 116 1.5× 27 0.4× 66 1.5k
Bethan Yates United Kingdom 7 812 1.0× 202 1.1× 41 0.5× 233 2.9× 80 1.1× 7 1.1k
Irene Papatheodorou United Kingdom 17 988 1.3× 166 0.9× 52 0.7× 163 2.1× 34 0.5× 45 1.4k
Nicolas Simonis Belgium 14 952 1.2× 203 1.1× 120 1.5× 96 1.2× 61 0.9× 18 1.1k
Andrey Alexeyenko Sweden 20 912 1.2× 154 0.8× 116 1.4× 180 2.3× 102 1.4× 42 1.4k
Ioannis Iliopoulos Greece 16 1.1k 1.4× 96 0.5× 93 1.2× 65 0.8× 96 1.4× 47 1.4k

Countries citing papers authored by Sara Ballouz

Since Specialization
Citations

This map shows the geographic impact of Sara Ballouz'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 Sara Ballouz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sara Ballouz more than expected).

Fields of papers citing papers by Sara Ballouz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sara Ballouz. 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 Sara Ballouz. The network helps show where Sara Ballouz may publish in the future.

Co-authorship network of co-authors of Sara Ballouz

This figure shows the co-authorship network connecting the top 25 collaborators of Sara Ballouz. A scholar is included among the top collaborators of Sara Ballouz 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 Sara Ballouz. Sara Ballouz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ballouz, Sara, Risa Karakida Kawaguchi, Maria T. Peña, et al.. (2023). The transcriptional legacy of developmental stochasticity. Nature Communications. 14(1). 7226–7226. 4 indexed citations
2.
Kaminow, Benjamin, Sara Ballouz, Jesse Gillis, & Alexander Dobin. (2022). Pan-human consensus genome significantly improves the accuracy of RNA-seq analyses. Genome Research. 32(4). 738–749. 8 indexed citations
3.
Ballouz, Sara, et al.. (2022). Variability of cross-tissue X-chromosome inactivation characterizes timing of human embryonic lineage specification events. Developmental Cell. 57(16). 1995–2008.e5. 20 indexed citations
4.
Lee, J. Jack, et al.. (2020). CoCoCoNet: conserved and comparative co-expression across a diverse set of species. Nucleic Acids Research. 48(W1). W566–W571. 28 indexed citations
5.
Pang, Chi Nam Ignatius, Sara Ballouz, L Thibaut, et al.. (2020). Analytical Guidelines for co-fractionation Mass Spectrometry Obtained through Global Profiling of Gold Standard Saccharomyces cerevisiae Protein Complexes. Molecular & Cellular Proteomics. 19(11). 1876–1895. 15 indexed citations
6.
Ballouz, Sara, Alexander Dobin, & Jesse Gillis. (2019). Is it time to change the reference genome?. Genome biology. 20(1). 159–159. 110 indexed citations
7.
Crow, Megan, Nathaniel C. Lim, Sara Ballouz, Paul Pavlidis, & Jesse Gillis. (2019). Predictability of human differential gene expression. Proceedings of the National Academy of Sciences. 116(13). 6491–6500. 76 indexed citations
8.
Crow, Megan, Anirban Paul, Sara Ballouz, Zhi Huang, & Jesse Gillis. (2018). Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor. Nature Communications. 9(1). 884–884. 165 indexed citations
9.
Ballouz, Sara & Jesse Gillis. (2017). Strength of functional signature correlates with effect size in autism. Genome Medicine. 9(1). 64–64. 7 indexed citations
10.
Ballouz, Sara, Melanie Weber, Paul Pavlidis, & Jesse Gillis. (2016). EGAD: ultra-fast functional analysis of gene networks. Bioinformatics. 33(4). 612–614. 54 indexed citations
11.
O’Meara, Matthew J., Sara Ballouz, Brian K. Shoichet, & Jesse Gillis. (2016). Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction. PLoS ONE. 11(7). e0160098–e0160098. 12 indexed citations
12.
Ballouz, Sara & Jesse Gillis. (2016). AuPairWise: A Method to Estimate RNA-Seq Replicability through Co-expression. PLoS Computational Biology. 12(4). e1004868–e1004868. 6 indexed citations
13.
Ballouz, Sara, Paul Pavlidis, & Jesse Gillis. (2016). Using predictive specificity to determine when gene set analysis is biologically meaningful. Nucleic Acids Research. 45(4). gkw957–gkw957. 20 indexed citations
14.
Crow, Megan, Anirban Paul, Sara Ballouz, Zheng Huang, & Jesse Gillis. (2016). Exploiting single-cell expression to characterize co-expression replicability. Genome biology. 17(1). 101–101. 47 indexed citations
15.
Ballouz, Sara, K. Mohanasundaram, Richard A. George, et al.. (2015). Novel therapeutics for coronary artery disease from genome-wide association study data. BMC Medical Genomics. 8(S2). S1–S1. 27 indexed citations
16.
Gillis, Jesse, Sara Ballouz, & Paul Pavlidis. (2014). Bias tradeoffs in the creation and analysis of protein–protein interaction networks. Journal of Proteomics. 100. 44–54. 48 indexed citations
17.
Ballouz, Sara, Jason Y. Liu, Richard A. George, et al.. (2013). GentrepidV2.0: a web server for candidate disease gene prediction. BMC Bioinformatics. 14(1). 249–249. 4 indexed citations
18.
Ballouz, Sara, Jason Y. Liu, Martin Oti, et al.. (2011). Analysis of genome-wide association study data using the protein knowledge base. BMC Genetics. 12(1). 98–98. 8 indexed citations
19.
Ballouz, Sara, Andrew Francis, Ruiting Lan, & Mark M. Tanaka. (2010). Conditions for the Evolution of Gene Clusters in Bacterial Genomes. PLoS Computational Biology. 6(2). e1000672–e1000672. 47 indexed citations
20.
Teber, Erdahl, Jason Y. Liu, Sara Ballouz, Diane Fatkin, & Merridee A. Wouters. (2009). Comparison of automated candidate gene prediction systems using genes implicated in type 2 diabetes by genome-wide association studies. BMC Bioinformatics. 10(S1). S69–S69. 29 indexed citations

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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