Allegra M. Lord

4.6k total citations · 3 hit papers
17 papers, 3.5k citations indexed

About

Allegra M. Lord is a scholar working on Hematology, Molecular Biology and Cell Biology. According to data from OpenAlex, Allegra M. Lord has authored 17 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Hematology, 9 papers in Molecular Biology and 5 papers in Cell Biology. Recurrent topics in Allegra M. Lord's work include Zebrafish Biomedical Research Applications (5 papers), Hematopoietic Stem Cell Transplantation (5 papers) and Acute Myeloid Leukemia Research (4 papers). Allegra M. Lord is often cited by papers focused on Zebrafish Biomedical Research Applications (5 papers), Hematopoietic Stem Cell Transplantation (5 papers) and Acute Myeloid Leukemia Research (4 papers). Allegra M. Lord collaborates with scholars based in United States, United Kingdom and Sweden. Allegra M. Lord's co-authors include Trista E. North, Leonard I. Zon, Wolfram Goessling, George Q. Daley, Gerhard Weber, Randall T. Moon, Mark Puder, Gilbert Weidinger, Benjamin L. Ebert and Garret A. FitzGerald and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Allegra M. Lord

17 papers receiving 3.5k citations

Hit Papers

Prostaglandin E2 regulates vertebrate haematopoietic stem... 2007 2026 2013 2019 2007 2009 2014 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Allegra M. Lord United States 12 2.0k 1.4k 906 707 648 17 3.5k
Stephen J. P. Pratt United States 25 2.5k 1.3× 1.3k 0.9× 1.6k 1.8× 905 1.3× 570 0.9× 52 4.7k
Paul D. Kingsley United States 31 2.3k 1.2× 587 0.4× 950 1.0× 374 0.5× 776 1.2× 68 3.7k
Nicola K. Wilson United Kingdom 31 2.8k 1.4× 1.2k 0.9× 787 0.9× 256 0.4× 1.1k 1.7× 64 3.9k
Michael J. Ferkowicz United States 22 2.0k 1.0× 411 0.3× 726 0.8× 460 0.7× 485 0.7× 37 3.2k
C. Glenn Begley Australia 33 2.0k 1.0× 1.9k 1.4× 944 1.0× 610 0.9× 1.0k 1.6× 73 4.5k
Tomomasa Yokomizo Japan 24 1.7k 0.8× 822 0.6× 1.4k 1.6× 211 0.3× 773 1.2× 48 2.8k
Masako Ohmura Japan 18 1.8k 0.9× 1.3k 1.0× 250 0.3× 678 1.0× 774 1.2× 29 3.8k
Anna Savoia Italy 38 1.7k 0.9× 1.7k 1.3× 289 0.3× 533 0.8× 406 0.6× 121 4.1k
Kentaro Hosokawa Japan 17 1.8k 0.9× 1.7k 1.2× 249 0.3× 761 1.1× 888 1.4× 28 3.7k
Sahoko Matsuoka Japan 18 2.5k 1.3× 2.6k 1.9× 589 0.7× 1.2k 1.7× 1.4k 2.1× 29 5.4k

Countries citing papers authored by Allegra M. Lord

Since Specialization
Citations

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

Fields of papers citing papers by Allegra M. Lord

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Allegra M. Lord. 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 Allegra M. Lord. The network helps show where Allegra M. Lord may publish in the future.

Co-authorship network of co-authors of Allegra M. Lord

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

All Works

17 of 17 papers shown
1.
Wojtowicz, Edyta E., Jayna J. Mistry, Charlotte Hellmich, et al.. (2023). Panhematopoietic RNA barcoding enables kinetic measurements of nucleate and anucleate lineages and the activation of myeloid clones following acute platelet depletion. Genome biology. 24(1). 152–152. 3 indexed citations
2.
Cahill, Thomas J., Xin Sun, Christophe Ravaud, et al.. (2021). Tissue-resident macrophages regulate lymphatic vessel growth and patterning in the developing heart. Development. 148(3). 70 indexed citations
3.
Carrelha, Joana, Yiran Meng, Laura M. Kettyle, et al.. (2018). Hierarchically Related Lineage-Restricted Fates of Multipotent Hematopoietic Stem Cells. Experimental Hematology. 64. S57–S58. 1 indexed citations
4.
Carrelha, Joana, Yiran Meng, Laura M. Kettyle, et al.. (2018). Hierarchically related lineage-restricted fates of multipotent haematopoietic stem cells. Nature. 554(7690). 106–111. 252 indexed citations
5.
Obeng, Esther A., Michael Seiler, Michelle C. Chen, et al.. (2016). Physiologic Expression of Sf3b1 K700E Causes Impaired Erythropoiesis, Aberrant Splicing, and Sensitivity to Therapeutic Spliceosome Modulation. Cancer Cell. 30(3). 404–417. 263 indexed citations
6.
Schneider, Rebekka K., Vera Ademà, Dirk Heckl, et al.. (2014). Role of Casein Kinase 1A1 in the Biology and Targeted Therapy of del(5q) MDS. Cancer Cell. 26(4). 509–520. 137 indexed citations
7.
Lord, Allegra M., Kendell Clement, Rebekka K. Schneider, et al.. (2014). Loss of TET2 Function in Myelodysplastic Syndrome Results in Intragenic Hypermethylation and Alterations in mRNA Splicing. Blood. 124(21). 775–775. 2 indexed citations
8.
Bejar, Rafael, Allegra M. Lord, Kristen E. Stevenson, et al.. (2014). TET2 mutations predict response to hypomethylating agents in myelodysplastic syndrome patients. Blood. 124(17). 2705–2712. 405 indexed citations breakdown →
9.
Mullally, Ann, Steven Lane, Brian Ball, et al.. (2010). Physiological Jak2V617F Expression Causes a Lethal Myeloproliferative Neoplasm with Differential Effects on Hematopoietic Stem and Progenitor Cells. Cancer Cell. 17(6). 584–596. 285 indexed citations
10.
North, Trista E., I. Ramesh Babu, Allegra M. Lord, et al.. (2010). PGE2-regulated wnt signaling andN-acetylcysteine are synergistically hepatoprotective in zebrafish acetaminophen injury. Proceedings of the National Academy of Sciences. 107(40). 17315–17320. 126 indexed citations
11.
Goessling, Wolfram, Trista E. North, Sabine Loewer, et al.. (2009). Genetic Interaction of PGE2 and Wnt Signaling Regulates Developmental Specification of Stem Cells and Regeneration. Cell. 136(6). 1136–1147. 580 indexed citations breakdown →
12.
North, Trista E., Wolfram Goessling, Marian Peeters, et al.. (2009). Hematopoietic Stem Cell Development Is Dependent on Blood Flow. Cell. 137(4). 736–748. 347 indexed citations
13.
Goessling, Wolfram, Trista E. North, Allegra M. Lord, et al.. (2008). APC mutant zebrafish uncover a changing temporal requirement for wnt signaling in liver development. Developmental Biology. 320(1). 161–174. 157 indexed citations
14.
North, Trista E., Wolfram Goessling, Marian Peeters, et al.. (2008). Hematopoietic Stem Cell Development Is Dependent on Blood Flow and Nitric Oxide Signaling. Blood. 112(11). 728–728. 1 indexed citations
15.
North, Trista E., Wolfram Goessling, Carl R. Walkley, et al.. (2007). Prostaglandin E2 regulates vertebrate haematopoietic stem cell homeostasis. Nature. 447(7147). 1007–1011. 862 indexed citations breakdown →
16.
Lord, Allegra M., Trista E. North, & Leonard I. Zon. (2007). Prostaglandin E2: Making More of Your Marrow. Cell Cycle. 6(24). 3054–3057. 41 indexed citations
17.

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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