Michael W. Lutz

5.8k total citations
152 papers, 3.6k citations indexed

About

Michael W. Lutz is a scholar working on Molecular Biology, Physiology and Psychiatry and Mental health. According to data from OpenAlex, Michael W. Lutz has authored 152 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Molecular Biology, 48 papers in Physiology and 32 papers in Psychiatry and Mental health. Recurrent topics in Michael W. Lutz's work include Alzheimer's disease research and treatments (42 papers), Dementia and Cognitive Impairment Research (31 papers) and Bioinformatics and Genomic Networks (25 papers). Michael W. Lutz is often cited by papers focused on Alzheimer's disease research and treatments (42 papers), Dementia and Cognitive Impairment Research (31 papers) and Bioinformatics and Genomic Networks (25 papers). Michael W. Lutz collaborates with scholars based in United States, United Kingdom and Germany. Michael W. Lutz's co-authors include Allen D. Roses, Ann M. Saunders, Paul H. Morgan, Terry Kenakin, Donna G. Crenshaw, Ornit Chiba‐Falek, Kathleen A. Welsh‐Bohmer, Daniel K. Burns, William Gottschalk and Scott S. Sundseth and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Neurology.

In The Last Decade

Michael W. Lutz

142 papers receiving 3.5k citations

Peers

Michael W. Lutz

PHYSI

PMH

CMN

GENET

Petroula Proitsi United Kingdom

Naoyuki Sato Japan

Amrita K. Cheema United States

Huiping Jiang China

Min Chen China

Toshikazu Saito Japan

Aiyi Liu United States

Takaaki Abe Japan

Jessica Lasky‐Su United States

Feng Bai China

Petroula Proitsi United Kingdom

Michael W. Lutz

1.3k ×0.8

1.3k ×1.1

PHYSI

548 ×0.9

PMH

206 ×0.4

CMN

384 ×1.0

GENET

Citations per year, relative to Michael W. Lutz Michael W. Lutz (= 1×) peers Petroula Proitsi

Countries citing papers authored by Michael W. Lutz

Since Specialization

Citations

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

Fields of papers citing papers by Michael W. Lutz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael W. Lutz. 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 Michael W. Lutz. The network helps show where Michael W. Lutz may publish in the future.

Co-authorship network of co-authors of Michael W. Lutz

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

All Works

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20 of 20 papers shown

Tognetti, Marco, Roland Bruderer, Lukas Reiter, et al.. (2025). Unveiling proteomic and peptide-level modifications in cerebrospinal fluid and plasma in normal cognitive aging. Communications Medicine. 5(1). 474–474.

Lutz, Michael W. & Ornit Chiba‐Falek. (2023). Bioinformatics pipeline to guide post‐GWAS studies in Alzheimer's: A new catalogue of disease candidate short structural variants. Alzheimer s & Dementia. 19(9). 4094–4109. 1 indexed citations

Ly, Alexander, Johnny van Doorn, Eric‐Jan Wagenmakers, et al.. (2022). A Bayesian perspective on Biogen's aducanumab trial. Alzheimer s & Dementia. 18(11). 2341–2351. 8 indexed citations

Gable, Karissa, Stojan Perić, Michael W. Lutz, et al.. (2022). A longitudinal evaluation of fatigue in chronic inflammatory demyelinating polyneuropathy. Brain and Behavior. 12(8). e2712–e2712. 4 indexed citations

Kimbrough, Dorlan, et al.. (2022). Neuromyelitis optica: Clinical course and potential prognostic indicators. Multiple Sclerosis and Related Disorders. 69. 104414–104414. 5 indexed citations

Bryan, Jordan, William Gottschalk, Alexandra Badea, et al.. (2021). Likelihood ratio statistics for gene set enrichment in Alzheimer's disease pathways. Alzheimer s & Dementia. 17(4). 561–573. 2 indexed citations

Li, Tianqi, Colleen Pappas, Brandon S. Klinedinst, et al.. (2021). APOE, TOMM40, and sex interactions on neural network connectivity. Neurobiology of Aging. 109. 158–165. 14 indexed citations

Lutz, Michael W., et al.. (2020). A Course for Developing Personal Software Engineering Competencies. Papers on Engineering Education Repository (American Society for Engineering Education). 25.33.1–25.33.19.

Flynn, Loren L., Ryan S. Anderton, Frank Mastaglia, et al.. (2020). Disease-modifying effects of an SCAF4 structural variant in a predominantly SOD1 ALS cohort. Neurology Genetics. 6(4). 8 indexed citations

10.

Lutz, Michael W., et al.. (2020). Shared genetic etiology underlying Alzheimer’s disease and major depressive disorder. Translational Psychiatry. 10(1). 88–88. 47 indexed citations

11.

Lutz, Michael W., Donna G. Crenshaw, Kathleen A. Welsh‐Bohmer, Daniel K. Burns, & Allen D. Roses. (2016). New Genetic Approaches to AD: Lessons from APOE-TOMM40 Phylogenetics. Current Neurology and Neuroscience Reports. 16(5). 48–48. 27 indexed citations

12.

Gottschalk, William, Michael W. Lutz, Yu He, et al.. (2014). Journal of Parkinson’s disease & Alzheimer’s disease. PubMed. 1(1). 67 indexed citations

13.

Greenbaum, Lior, Michael W. Lutz, Anthony Heymann, et al.. (2014). The TOMM40 poly-T rs10524523 variant is associated with cognitive performance among non-demented elderly with type 2 diabetes. European Neuropsychopharmacology. 24(9). 1492–1499. 22 indexed citations

14.

Roses, Allen D., Michael W. Lutz, Donna G. Crenshaw, et al.. (2013). TOMM40 and APOE: Requirements for replication studies of association with age of disease onset and enrichment of a clinical trial. Alzheimer s & Dementia. 9(2). 132–136. 53 indexed citations

15.

Caselli, Richard J., Amylou C. Dueck, Matthew J. Huentelman, et al.. (2012). Longitudinal modeling of cognitive aging and the TOMM40 effect. Alzheimer s & Dementia. 8(6). 490–495. 58 indexed citations

16.

Linnertz, Colton L., Ann M. Saunders, Michael W. Lutz, et al.. (2012). Characterization of the Poly-T Variant in the TOMM40 Gene in Diverse Populations. PLoS ONE. 7(2). e30994–e30994. 46 indexed citations

17.

Lutz, Michael W., et al.. (2012). Code lists for interoperability - Principles and best practices in INSPIRE. EGUGA. 10415. 1 indexed citations

18.

Roses, Allen D., Michael W. Lutz, Heather Amrine‐Madsen, et al.. (2009). A TOMM40 variable-length polymorphism predicts the age of late-onset Alzheimer's disease. The Pharmacogenomics Journal. 10(5). 375–384. 288 indexed citations

19.

Luka, Henryk, Michael W. Lutz, Theo Blick, & Lukas Pfiffner. (2001). Einfluss von eingesäten Wildblumenstreifen auf die epigäischen Lautkäferrind Spinnen (Carabidaeund Araneae) in der intensiv genutzten Agrarlandschaft "Grosses Moos",Schweiz. Organic Eprints (International Centre for Research in Organic Food Systems, and Research Institute of Organic Agriculture). 3 indexed citations

20.

Hammond, W. E., et al.. (1984). TMR — Meeting the Demand for the Variety of Report Modalities. PubMed Central. 421–424. 3 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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