Alec Witty

2.1k total citations · 1 hit paper
8 papers, 1.1k citations indexed

About

Alec Witty is a scholar working on Molecular Biology, Oncology and Surgery. According to data from OpenAlex, Alec Witty has authored 8 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Oncology and 2 papers in Surgery. Recurrent topics in Alec Witty's work include Congenital heart defects research (4 papers), CAR-T cell therapy research (4 papers) and Pluripotent Stem Cells Research (2 papers). Alec Witty is often cited by papers focused on Congenital heart defects research (4 papers), CAR-T cell therapy research (4 papers) and Pluripotent Stem Cells Research (2 papers). Alec Witty collaborates with scholars based in United States and Canada. Alec Witty's co-authors include Gordon Keller, Steven Kattman, Nicole Dubois, Akitsu Hotta, James Ellis, Mark Gagliardi, Maryam Niapour, Roger Y. Tam, Anton Mihic and Ren‐Ke Li and has published in prestigious journals such as Blood, Nature Biotechnology and Cell stem cell.

In The Last Decade

Alec Witty

7 papers receiving 1.1k 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.

Stage-Specific Optimization of Activin/Nodal and BMP Signaling Promotes Cardiac Differentiation of Mouse and Human Pluripotent Stem Cell Lines

2011 855 citations Steven Kattman, Alec Witty et al. Cell stem cell profile →

Peers

Alec Witty

MB

SURGE

BE

CMN

BIOMA

Misato Nishikawa Japan

Jeremy I. Pearl United States

Marcelo C. Ribeiro Netherlands

Sylvia Merkert Germany

Seung‐Cheol Choi South Korea

Sunita L. D’Souza United States

Aditya Kumar United States

Sandra Petrus-Reurer Sweden

Francijna E. van den Hil Netherlands

Giselle Galang United States

Misato Nishikawa Japan

Alec Witty

711 ×0.7

MB

253 ×0.5

SURGE

116 ×0.6

BE

94 ×0.7

CMN

49 ×0.5

BIOMA

Citations per year, relative to Alec Witty Alec Witty (= 1×) peers Misato Nishikawa

Countries citing papers authored by Alec Witty

Since Specialization

Citations

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

Fields of papers citing papers by Alec Witty

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alec Witty

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

All Works

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8 of 8 papers shown

1.

Cichocki, Frank, Ryan Bjordahl, Sajid Mahmood, et al.. (2022). Dual antigen–targeted off-the-shelf NK cells show durable response and prevent antigen escape in lymphoma and leukemia. Blood. 140(23). 2451–2462. 58 indexed citations

2.

Yzaguirre, Amanda D., et al.. (2022). CD82 Is Sufficient to Uniquely Identify Pluripotent Stem Cell-Derived Hemogenic Endothelium with the Hematopoietic Lineage Potency to Give Rise to Bona Fide Lymphocytes. Blood. 140(Supplement 1). 5728–5729.

3.

Yang, Bi-Huei, Wen-I Yeh, Mochtar Pribadi, et al.. (2021). Combination of Three Unique Anti-Tumor Modalities Engineered into iPSC-Derived T Cells Demonstrate a Synergistic Effect in Overcoming Tumor Heterogeneity and Cancer Escape. Blood. 138(Supplement 1). 2793–2793. 4 indexed citations

4.

Peralta, Eigen, Chia‐Wei Chang, Wen-I Yeh, et al.. (2020). Multiplexed Engineered, Off-the-Shelf T Cells Carrying Three Tumor-Associated Antigen-Targeting Modalities: CAR + Pan-Tumor Targeting TCR + CD16 Fc Receptor. Blood. 136(Supplement 1). 32–32. 1 indexed citations

5.

Ren, Jie, Peidong Han, Xuanyi Ma, et al.. (2019). Canonical Wnt5b Signaling Directs Outlying Nkx2.5+ Mesoderm into Pacemaker Cardiomyocytes. Developmental Cell. 50(6). 729–743.e5. 56 indexed citations

6.

Yoon, Charles, Hannah Song, Ting Yin, et al.. (2017). FZD4 Marks Lateral Plate Mesoderm and Signals with NORRIN to Increase Cardiomyocyte Induction from Pluripotent Stem Cell-Derived Cardiac Progenitors. Stem Cell Reports. 10(1). 87–100. 24 indexed citations

7.

Witty, Alec, Anton Mihic, Roger Y. Tam, et al.. (2014). Generation of the epicardial lineage from human pluripotent stem cells. Nature Biotechnology. 32(10). 1026–1035. 129 indexed citations

8.

Kattman, Steven, Alec Witty, Mark Gagliardi, et al.. (2011). Stage-Specific Optimization of Activin/Nodal and BMP Signaling Promotes Cardiac Differentiation of Mouse and Human Pluripotent Stem Cell Lines. Cell stem cell. 8(2). 228–240. 855 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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