Salvador Macip

3.6k total citations · 1 hit paper
62 papers, 2.6k citations indexed

About

Salvador Macip is a scholar working on Molecular Biology, Oncology and Genetics. According to data from OpenAlex, Salvador Macip has authored 62 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Molecular Biology, 20 papers in Oncology and 12 papers in Genetics. Recurrent topics in Salvador Macip's work include Cancer-related Molecular Pathways (14 papers), Chronic Lymphocytic Leukemia Research (12 papers) and Telomeres, Telomerase, and Senescence (9 papers). Salvador Macip is often cited by papers focused on Cancer-related Molecular Pathways (14 papers), Chronic Lymphocytic Leukemia Research (12 papers) and Telomeres, Telomerase, and Senescence (9 papers). Salvador Macip collaborates with scholars based in United Kingdom, Spain and United States. Salvador Macip's co-authors include Sam W. Lee, Stuart A. Aaronson, Mohammad Althubiti, Jian Yu, Makoto Igarashi, Petra Berggren, Miran Rada, George D.D. Jones, Marta Poblocka and Junji Sagara and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Experimental Medicine and The EMBO Journal.

In The Last Decade

Salvador Macip

59 papers receiving 2.6k 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.

The BCL2 family: from apoptosis mechanisms to new advances in targeted therapy

2025 56 citations Meike Vogler, Victoria M. Smith et al. profile →

Peers

Salvador Macip

MB

PHYSI

ONCOL

IMMUN

CR

Liqin Wang China

Sara Huerta‐Yépez Mexico

Masood A. Shammas United States

Julián Gómez-Cambronero United States

Yue Huang China

Yingxin Zhao United States

Megan Cully United Kingdom

Matteo Parri Italy

Douglas Lazarus United States

Adriana Borriello Italy

Liqin Wang China

Salvador Macip

1.7k ×1.1

MB

439 ×0.8

PHYSI

473 ×0.9

ONCOL

509 ×1.0

IMMUN

445 ×1.2

CR

Citations per year, relative to Salvador Macip Salvador Macip (= 1×) peers Liqin Wang

Countries citing papers authored by Salvador Macip

Since Specialization

Citations

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

Fields of papers citing papers by Salvador Macip

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Salvador Macip

This figure shows the co-authorship network connecting the top 25 collaborators of Salvador Macip. A scholar is included among the top collaborators of Salvador Macip 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 Salvador Macip. Salvador Macip 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:

20 of 20 papers shown

1.

Cao, Thong Huy, Sandrine Jayne, Martin J.S. Dyer, et al.. (2025). Targeted Degradation of Class 1 HDACs With PROTACs is Highly Effective at Inducing DLBCL Cell Death. eJHaem. 6(4). e70127–e70127.

2.

Basran, Jaswir, Hanna Kwon, Aneika C. Leney, et al.. (2024). Characterizing the protein–protein interaction between MDM2 and 14-3-3σ; proof of concept for small molecule stabilization. Journal of Biological Chemistry. 300(2). 105651–105651. 5 indexed citations

3.

Macip, Salvador, et al.. (2024). Effects of Fasting on THP1 Macrophage Metabolism and Inflammatory Profile. International Journal of Molecular Sciences. 25(16). 9029–9029. 1 indexed citations

4.

Piletska, Elena, Dana L. Thompson, Rebecca M. Jones, et al.. (2022). Snapshot imprinting as a tool for surface mapping and identification of novel biomarkers of senescent cells. Nanoscale Advances. 4(24). 5304–5311. 5 indexed citations

5.

Piletsky, Stanislav, Elena Piletska, Marta Poblocka, et al.. (2021). Snapshot imprinting: rapid identification of cancer cell surface proteins and epitopes using molecularly imprinted polymers. Nano Today. 41. 101304–101304. 37 indexed citations

6.

Macip, Salvador, et al.. (2021). A master of all trades – linking retinoids to different signalling pathways through the multi-purpose receptor STRA6. Cell Death Discovery. 7(1). 358–358. 18 indexed citations

7.

Polymeros, Konstantinos, et al.. (2020). Differences in the molecular profile of endometrial cancers from British White and British South Asian women. PLoS ONE. 15(6). e0233900–e0233900. 5 indexed citations

8.

Kaur, Amanpreet, Salvador Macip, & Cordula Stover. (2020). An Appraisal on the Value of Using Nutraceutical Based Senolytics and Senostatics in Aging. Frontiers in Cell and Developmental Biology. 8. 218–218. 19 indexed citations

9.

Jones, Donald J. L., et al.. (2019). Radiotherapy-Induced Senescence and its Effects on Responses to Treatment. Clinical Oncology. 31(5). 283–289. 33 indexed citations

10.

Smith, Victoria M., Anna Dietz, Sjoerd J. L. van Wijk, et al.. (2019). Specific interactions of BCL-2 family proteins mediate sensitivity to BH3-mimetics in diffuse large B-cell lymphoma. Haematologica. 105(8). 2150–2163. 27 indexed citations

11.

Rada, Miran, Nickolai A. Barlev, & Salvador Macip. (2018). BTK modulates p73 activity to induce apoptosis independently of p53. Cell Death Discovery. 4(1). 30–30. 21 indexed citations

12.

Althubiti, Mohammad, Miran Rada, Koon-Guan Lee, et al.. (2016). BTK Modulates p53 Activity to Enhance Apoptotic and Senescent Responses. Cancer Research. 76(18). 5405–5414. 48 indexed citations

13.

Rada, Miran, Е. А. Васильева, Larissa Lezina, et al.. (2016). Human EHMT2/G9a activates p53 through methylation-independent mechanism. Oncogene. 36(7). 922–932. 42 indexed citations

14.

Willmott, Chris & Salvador Macip. (2016). Where Science and Ethics Meet. 1 indexed citations

15.

Jones, George D.D., et al.. (2013). Stra6, a retinoic acid-responsive gene, participates in p53-induced apoptosis after DNA damage. Cell Death and Differentiation. 20(7). 910–919. 32 indexed citations

16.

Muñoz‐Fontela, César, Salvador Macip, Luis Martínez‐Sobrido, et al.. (2008). Transcriptional role of p53 in interferon-mediated antiviral immunity. The Journal of Experimental Medicine. 205(8). 1929–1938. 193 indexed citations

17.

Tan, Maria, Lorenzo Battini, Ana C. Tuyama, et al.. (2006). Characterization of human metapneumovirus infection of myeloid dendritic cells. Virology. 357(1). 1–9. 18 indexed citations

18.

Macip, Salvador, et al.. (2005). Human Parainfluenza Virus 3 Neuraminidase Activity Contributes to Dendritic Cell Maturation. Viral Immunology. 18(3). 523–533. 3 indexed citations

19.

Ohtsuka, Takao, Hoon Ryu, Yoji Andrew Minamishima, et al.. (2004). ASC is a Bax adaptor and regulates the p53–Bax mitochondrial apoptosis pathway. Nature Cell Biology. 6(2). 121–128. 206 indexed citations

20.

Macip, Salvador. (2002). Inhibition of p21-mediated ROS accumulation can rescue p21-induced senescence. The EMBO Journal. 21(9). 2180–2188. 303 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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