Mark Bieda

7.1k total citations
22 papers, 1.3k citations indexed

About

Mark Bieda is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Oncology. According to data from OpenAlex, Mark Bieda has authored 22 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 6 papers in Cellular and Molecular Neuroscience and 4 papers in Oncology. Recurrent topics in Mark Bieda's work include Neuroscience and Neuropharmacology Research (5 papers), Epigenetics and DNA Methylation (5 papers) and Photoreceptor and optogenetics research (3 papers). Mark Bieda is often cited by papers focused on Neuroscience and Neuropharmacology Research (5 papers), Epigenetics and DNA Methylation (5 papers) and Photoreceptor and optogenetics research (3 papers). Mark Bieda collaborates with scholars based in United States, Canada and Spain. Mark Bieda's co-authors include Peggy Farnham, Roland Green, Xiaoqin Xu, M Bruce MacIver, Michael Singer, David R. Copenhagen, Victor X. Jin, Janine M. LaSalle, Dag H. Yasui and Raman P. Nagarajan and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Mark Bieda

22 papers receiving 1.3k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Mark Bieda 980 358 218 175 148 22 1.3k
Arjan P.M. de Brouwer 1.6k 1.6× 923 2.6× 180 0.8× 155 0.9× 118 0.8× 77 2.4k
Tamar Paperna 524 0.5× 242 0.7× 124 0.6× 76 0.4× 124 0.8× 48 1.2k
Andrea L. Webber 1.1k 1.1× 495 1.4× 287 1.3× 132 0.8× 107 0.7× 28 1.5k
Rocío G. Urdinguio 1.3k 1.3× 486 1.4× 67 0.3× 92 0.5× 90 0.6× 33 1.6k
Luciana Musante 1.2k 1.3× 472 1.3× 147 0.7× 49 0.3× 190 1.3× 37 1.6k
Marie‐Christine Birling 1.0k 1.1× 403 1.1× 477 2.2× 124 0.7× 86 0.6× 61 1.8k
Keiko Nakanishi 583 0.6× 92 0.3× 184 0.8× 77 0.4× 111 0.8× 30 989
Ida Manna 510 0.5× 162 0.5× 331 1.5× 67 0.4× 111 0.8× 52 1.2k
Koen L.I. van Gassen 564 0.6× 407 1.1× 319 1.5× 50 0.3× 70 0.5× 42 1.3k
Marcel W. Coolen 1.2k 1.2× 272 0.8× 128 0.6× 59 0.3× 67 0.5× 23 1.6k

Countries citing papers authored by Mark Bieda

Since Specialization
Citations

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

Fields of papers citing papers by Mark Bieda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Bieda

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

All Works

20 of 20 papers shown
1.
Strickler, John H., Andrea Cercek, Kimmie Ng, et al.. (2023). 551O Impact of baseline molecular alterations on the efficacy of tucatinib (TUC) plus trastuzumab (Tras) for HER2+, RAS WT metastatic CRC (mCRC) in MOUNTAINEER. Annals of Oncology. 34. S411–S412. 2 indexed citations
2.
Strickler, John H., Andrea Cercek, Kimmie Ng, et al.. (2023). HER2 testing in the MOUNTAINEER trial: Analysis of treatment response based on central HER2 assessment using IHC/ISH and NGS.. Journal of Clinical Oncology. 41(16_suppl). 3528–3528. 5 indexed citations
3.
Gray, Elizabeth, Kelly Hensley, Esther S. Trueblood, et al.. (2020). 617 Tisotumab vedotin shows immunomodulatory activity through induction of immunogenic cell death. SHILAP Revista de lepidopterología. A371–A372. 7 indexed citations
4.
Kolisnik, Tyler, et al.. (2016). Reusable, extensible, and modifiable R scripts and Kepler workflows for comprehensive single set ChIP-seq analysis. BMC Bioinformatics. 17(1). 270–270. 1 indexed citations
5.
Leigh, Richard, Mahmoud Mostafa, Elizabeth M. King, et al.. (2016). An inhaled dose of budesonide induces genes involved in transcription and signaling in the human airways: enhancement of anti‐ and proinflammatory effector genes. Pharmacology Research & Perspectives. 4(4). e00243–e00243. 45 indexed citations
6.
7.
Padmanabhan, Nisha, Xuchu Wu, Anne C. Ferguson‐Smith, et al.. (2013). Mutation in Folate Metabolism Causes Epigenetic Instability and Transgenerational Effects on Development. Cell. 155(1). 81–93. 183 indexed citations
8.
McPhillips, Timothy, et al.. (2012). Workflows for microarray data processing in the Kepler environment. BMC Bioinformatics. 13(1). 102–102. 11 indexed citations
9.
Bieda, Mark. (2012). Kepler for ‘Omics Bioinformatics. Procedia Computer Science. 9. 1635–1638. 2 indexed citations
10.
Bieda, Mark, Henry K. Su, & M Bruce MacIver. (2009). Anesthetics Discriminate Between Tonic and Phasic γ-Aminobutyric Acid Receptors on Hippocampal CA1 Neurons. Anesthesia & Analgesia. 108(2). 484–490. 33 indexed citations
11.
Bieda, Mark, et al.. (2008). Analysis of the Mechanisms Mediating Tumor-Specific Changes in Gene Expression in Human Liver Tumors. Cancer Research. 68(8). 2641–2651. 36 indexed citations
12.
Xu, Xiaoqin, Mark Bieda, Victor X. Jin, et al.. (2007). A comprehensive ChIP–chip analysis of E2F1, E2F4, and E2F6 in normal and tumor cells reveals interchangeable roles of E2F family members. Genome Research. 17(11). 1550–1561. 171 indexed citations
13.
Krig, Sheryl R., Victor X. Jin, Mark Bieda, et al.. (2007). Identification of Genes Directly Regulated by the Oncogene ZNF217 Using Chromatin Immunoprecipitation (ChIP)-Chip Assays. Journal of Biological Chemistry. 282(13). 9703–9712. 67 indexed citations
14.
Bieda, Mark, Xiaoqin Xu, Michael Singer, Roland Green, & Peggy Farnham. (2006). Unbiased location analysis of E2F1-binding sites suggests a widespread role for E2F1 in the human genome. Genome Research. 16(5). 595–605. 268 indexed citations
15.
Bieda, Mark & David R. Copenhagen. (2004). N-type and L-type calcium channels mediate glycinergic synaptic inputs to retinal ganglion cells of tiger salamanders. Visual Neuroscience. 21(4). 545–550. 14 indexed citations
16.
Bieda, Mark & M Bruce MacIver. (2004). Major Role For Tonic GABAA Conductances in Anesthetic Suppression of Intrinsic Neuronal Excitability. Journal of Neurophysiology. 92(3). 1658–1667. 105 indexed citations
17.
Bieda, Mark, et al.. (2002). Slow Diffusion into Brain Slices Decreases the Apparent Potency of an Anesthetic. Anesthesiology. 96(Sup 2). A790–A790. 1 indexed citations
18.
Bieda, Mark & David R. Copenhagen. (2000). Inhibition is not required for the production of transient spiking responses from retinal ganglion cells. Visual Neuroscience. 17(2). 243–254. 19 indexed citations
19.
Bieda, Mark & David R. Copenhagen. (1999). Sodium Action Potentials Are Not Required for Light-Evoked Release of GABA or Glycine From Retinal Amacrine Cells. Journal of Neurophysiology. 81(6). 3092–3095. 28 indexed citations
20.
Dixon, D., et al.. (1996). Quinine, intracellular pH and modulation of hemi-gap junctions in catfish horizontal cells. Vision Research. 36(24). 3925–3931. 28 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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