Brian Gudenas

932 total citations
12 papers, 223 citations indexed

About

Brian Gudenas is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Brian Gudenas has authored 12 papers receiving a total of 223 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 6 papers in Cancer Research and 3 papers in Genetics. Recurrent topics in Brian Gudenas's work include Cancer-related molecular mechanisms research (5 papers), RNA modifications and cancer (3 papers) and Glioma Diagnosis and Treatment (3 papers). Brian Gudenas is often cited by papers focused on Cancer-related molecular mechanisms research (5 papers), RNA modifications and cancer (3 papers) and Glioma Diagnosis and Treatment (3 papers). Brian Gudenas collaborates with scholars based in United States, Netherlands and Spain. Brian Gudenas's co-authors include Liangjiang Wang, Anand K. Srivastava, Paul A. Northcott, Shuzhen Kuang, Jun Wang, Jesús García-López, Rachelle R. Olsen, David Finkelstein, Kevin W. Freeman and Qiang Lü and has published in prestigious journals such as Blood, PLoS ONE and Scientific Reports.

In The Last Decade

Brian Gudenas

11 papers receiving 222 citations

Peers

Brian Gudenas
Julian A. Zagalak United Kingdom
Brian Gudenas
Citations per year, relative to Brian Gudenas Brian Gudenas (= 1×) peers Julian A. Zagalak

Countries citing papers authored by Brian Gudenas

Since Specialization
Citations

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

Fields of papers citing papers by Brian Gudenas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian Gudenas

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

All Works

12 of 12 papers shown
1.
Rauch, Sebastian, Stefan O. Reber, Montserrat Pérez-Salvia, et al.. (2024). Sky-1214, a Small Molecule Splicing Modulator Targeting FANCL and Fanci, Provides a New Mechanism of Action Targeting Multiple Myeloma and Non-Hodgkin's Lymphoma. Blood. 144(Supplement 1). 2784–2784. 1 indexed citations
2.
Schmidt, Christin, Sarah L. Cohen, Brian Gudenas, et al.. (2024). PRDM6 promotes medulloblastoma by repressing chromatin accessibility and altering gene expression. Scientific Reports. 14(1). 16074–16074. 5 indexed citations
3.
Rauch, Sebastian, Massimo Pregnolato, Leanne Berry, et al.. (2024). 116 (PB104): Preclinical characterization of SKY-1214, a small molecule splicing modulator of Fanconi Anemia pathway members for the treatment of multiple myeloma and non-Hodgkin’s lymphoma. European Journal of Cancer. 211. 114639–114639. 1 indexed citations
4.
Zhao, Miao, Anders Sundström, Thale Kristin Olsen, et al.. (2024). MDB-52. MYC-DRIVEN PEDIATRIC BRAIN TUMORS SHARE A COMMON PHOTORECEPTOR IDENTITY. Neuro-Oncology. 26(Supplement_4). 0–0. 1 indexed citations
5.
Inoue, Akira, Laura J. Janke, Brian Gudenas, et al.. (2021). A genetic mouse model with postnatal Nf1 and p53 loss recapitulates the histology and transcriptome of human malignant peripheral nerve sheath tumor. Neuro-Oncology Advances. 3(1). vdab129–vdab129. 5 indexed citations
6.
Qiu, Runxiang, Jun Wu, Brian Gudenas, et al.. (2021). Depletion of kinesin motor KIF20A to target cell fate control suppresses medulloblastoma tumour growth. Communications Biology. 4(1). 552–552. 9 indexed citations
7.
Liu, Anthony P. Y., Brent A. Orr, Bryan Li, et al.. (2020). WNT-activated embryonal tumors of the pineal region: ectopic medulloblastomas or a novel pineoblastoma subgroup?. Acta Neuropathologica. 140(4). 595–597. 5 indexed citations
8.
García-López, Jesús, Joel Otero, Rachelle R. Olsen, et al.. (2020). Large 1p36 Deletions Affecting Arid1a Locus Facilitate Mycn-Driven Oncogenesis in Neuroblastoma. Cell Reports. 30(2). 454–464.e5. 23 indexed citations
9.
Gudenas, Brian, et al.. (2019). Genomic data mining for functional annotation of human long noncoding RNAs. Journal of Zhejiang University SCIENCE B. 20(6). 476–487. 16 indexed citations
10.
Gudenas, Brian & Liangjiang Wang. (2018). Prediction of LncRNA Subcellular Localization with Deep Learning from Sequence Features. Scientific Reports. 8(1). 16385–16385. 116 indexed citations
11.
Gudenas, Brian, Anand K. Srivastava, & Liangjiang Wang. (2017). Integrative genomic analyses for identification and prioritization of long non-coding RNAs associated with autism. PLoS ONE. 12(5). e0178532–e0178532. 21 indexed citations
12.
Gudenas, Brian & Liangjiang Wang. (2015). Gene Coexpression Networks in Human Brain Developmental Transcriptomes Implicate the Association of Long Noncoding RNAs with Intellectual Disability. Bioinformatics and Biology Insights. 9s1(Suppl 1). BBI.S29435–BBI.S29435. 20 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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