Max Follettie

456 total citations
10 papers, 365 citations indexed

About

Max Follettie is a scholar working on Molecular Biology, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Max Follettie has authored 10 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Oncology and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Max Follettie's work include HER2/EGFR in Cancer Research (2 papers), NF-κB Signaling Pathways (2 papers) and Microbial Metabolic Engineering and Bioproduction (2 papers). Max Follettie is often cited by papers focused on HER2/EGFR in Cancer Research (2 papers), NF-κB Signaling Pathways (2 papers) and Microbial Metabolic Engineering and Bioproduction (2 papers). Max Follettie collaborates with scholars based in United States and Canada. Max Follettie's co-authors include Lourdes Toral‐Barza, Jiang Wu, Quazi Shakey, Boris Shor, Celine Shi, Ker Yu, Anthony J. Sinskey, Bernhard J. Eikmanns, Veronica Diesl and Robert J. Steffan and has published in prestigious journals such as Journal of Biological Chemistry, Cancer Research and Journal of Medicinal Chemistry.

In The Last Decade

Max Follettie

10 papers receiving 358 citations

Peers

Max Follettie

ONCOL

IMMUN

GENET

Daniel R. Goulet United States

Christelle Debeissat France

Prasad Sulkshane Israel

Pia T Johansen Denmark

Emily E. Fink United States

Jean‐François Launay France

Frances F. Diehl United States

Chia-Feng Tsai Taiwan

Hoai‐Nghia Nguyen Vietnam

Nhat D. Quach United States

Daniel R. Goulet United States

Max Follettie

199 ×0.7

76 ×1.0

ONCOL

48 ×1.1

IMMUN

25 ×0.7

22 ×0.8

GENET

Citations per year, relative to Max Follettie Max Follettie (= 1×) peers Daniel R. Goulet

Countries citing papers authored by Max Follettie

Since Specialization

Citations

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

Fields of papers citing papers by Max Follettie

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Max Follettie

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

All Works

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10 of 10 papers shown

Geles, Kenneth G., Yijie Gao, Latha Sridharan, et al.. (2015). Abstract 1697: Therapeutic targeting the NOTCH3 receptor with antibody drug conjugates. Cancer Research. 75(15_Supplement). 1697–1697. 5 indexed citations

Tan, Xingzhi, Guixian Jin, Jeremy S. Myers, et al.. (2013). Abstract 4629: Tumor cells selected for resistance to an antibody-drug conjugate retain sensitivity to ADCs with modified linkers and payloads.. Cancer Research. 73(8_Supplement). 4629–4629. 12 indexed citations

Dunn, David A., Donald Apanovitch, Max Follettie, Tao He, & Terence E. Ryan. (2010). Taking a Systems Approach to the Identification of Novel Therapeutic Targets and Biomarkers. Current Pharmaceutical Biotechnology. 11(7). 721–734. 5 indexed citations

Shor, Boris, Jiang Wu, Quazi Shakey, et al.. (2010). Requirement of the mTOR Kinase for the Regulation of Maf1 Phosphorylation and Control of RNA Polymerase III-dependent Transcription in Cancer Cells. Journal of Biological Chemistry. 285(20). 15380–15392. 146 indexed citations

Messersmith, Wells A., N.V. Rajeshkumar, Aik Choon Tan, et al.. (2009). Efficacy and pharmacodynamic effects of bosutinib (SKI-606), a Src/Abl inhibitor, in freshly generated human pancreas cancer xenografts. Molecular Cancer Therapeutics. 8(6). 1484–1493. 34 indexed citations

Dehnhardt, Christoph M., Aranapakam M. Venkatesan, Zecheng Chen, et al.. (2009). Design and Synthesis of Novel Diaminoquinazolines with in Vivo Efficacy for β-Catenin/T-Cell Transcriptional Factor 4 Pathway Inhibition. Journal of Medicinal Chemistry. 53(2). 897–910. 25 indexed citations

Zhang, Yixian, Judy Lucas, Sreekala Mandiyan, et al.. (2008). IκBα Kinase Inhibitor IKI-1 Conferred Tumor Necrosis Factor α Sensitivity to Pancreatic Cancer Cells and a Xenograft Tumor Model. Cancer Research. 68(22). 9519–9524. 12 indexed citations

Keith, James C., Leo Albert, Max Follettie, et al.. (2005). The utility of pathway selective estrogen receptor ligands that inhibit nuclear factor-κB transcriptional activity in models of rheumatoid arthritis. Arthritis Research & Therapy. 7(3). R427–38. 48 indexed citations

Kiss, Róbert, Gregory Stephanopoulos, & Max Follettie. (1990). Quantitative assay for low levels of L‐threonine in amino acid fermentation broths. Biotechnology and Bioengineering. 35(11). 1169–1173. 4 indexed citations

10.

Eikmanns, Bernhard J., et al.. (1989). The phosphoenolpyruvate carboxylase gene of Corynebacterium glutamicum: Molecular cloning, nucleotide sequence, and expression. Molecular and General Genetics MGG. 218(2). 330–339. 74 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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