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Citing this Article

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Published on 04.09.13 in Vol 1, No 2 (2013): Jul-Dec

This paper is in the following e-collection/theme issue:

Works citing "Development of a Smartphone App for a Genetics Website: The Amyotrophic Lateral Sclerosis Online Genetics Database (ALSoD)"

According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.2706):

(note that this is only a small subset of citations)

  1. Ryan M, Zaldívar Vaillant T, McLaughlin RL, Doherty MA, Rooney J, Heverin M, Gutierrez J, Lara-Fernández GE, Pita Rodríguez M, Hackembruch J, Perna A, Vazquez MC, Musio M, Ketzoian CN, Logroscino G, Hardiman O. Comparison of the clinical and genetic features of amyotrophic lateral sclerosis across Cuban, Uruguayan and Irish clinic-based populations. Journal of Neurology, Neurosurgery & Psychiatry 2019;90(6):659
    CrossRef
  2. Foggin S, Mesquita-Ribeiro R, Dajas-Bailador F, Layfield R. Biological Significance of microRNA Biomarkers in ALS—Innocent Bystanders or Disease Culprits?. Frontiers in Neurology 2019;10
    CrossRef
  3. Yin B, Balvert M, van der Spek RAA, Dutilh BE, Bohté S, Veldink J, Schönhuth A. Using the structure of genome data in the design of deep neural networks for predicting amyotrophic lateral sclerosis from genotype. Bioinformatics 2019;35(14):i538
    CrossRef
  4. Finegan E, Chipika RH, Li Hi Shing S, Doherty MA, Hengeveld JC, Vajda A, Donaghy C, McLaughlin RL, Pender N, Hardiman O, Bede P. The clinical and radiological profile of primary lateral sclerosis: a population-based study. Journal of Neurology 2019;
    CrossRef
  5. Prasad A, Bharathi V, Sivalingam V, Girdhar A, Patel BK. Molecular Mechanisms of TDP-43 Misfolding and Pathology in Amyotrophic Lateral Sclerosis. Frontiers in Molecular Neuroscience 2019;12
    CrossRef
  6. Ryan M, Heverin M, Doherty MA, Davis N, Corr EM, Vajda A, Pender N, McLaughlin R, Hardiman O. Determining the incidence of familiality in ALS. Neurology Genetics 2018;4(3):e239
    CrossRef
  7. Goyal VD, Magliery TJ. Phylogenetic spread of sequence data affects fitness of SOD1 consensus enzymes: Insights from sequence statistics and structural analyses. Proteins: Structure, Function, and Bioinformatics 2018;86(6):609
    CrossRef
  8. Tavella D, Zitzewitz JA, Massi F. Characterization of TDP-43 RRM2 Partially Folded States and Their Significance to ALS Pathogenesis. Biophysical Journal 2018;115(9):1673
    CrossRef
  9. Schmitt ND, Agar JN. Parsing disease-relevant protein modifications from epiphenomena: perspective on the structural basis of SOD1-mediated ALS. Journal of Mass Spectrometry 2017;52(7):480
    CrossRef
  10. De Marco G, Lomartire A, Calvo A, Risso A, De Luca E, Mostert M, Mandrioli J, Caponnetto C, Borghero G, Manera U, Canosa A, Moglia C, Restagno G, Fini N, Tarella C, Giordana MT, Rinaudo MT, Chiò A. Monocytes of patients with amyotrophic lateral sclerosis linked to gene mutations display altered TDP-43 subcellular distribution. Neuropathology and Applied Neurobiology 2017;43(2):133
    CrossRef
  11. Black HA, Leighton DJ, Cleary EM, Rose E, Stephenson L, Colville S, Ross D, Warner J, Porteous M, Gorrie GH, Swingler R, Goldstein D, Harms MB, Connick P, Pal S, Aitman TJ, Chandran S. Genetic epidemiology of motor neuron disease-associated variants in the Scottish population. Neurobiology of Aging 2017;51:178.e11
    CrossRef
  12. McAlary L, Aquilina JA, Yerbury JJ. Susceptibility of Mutant SOD1 to Form a Destabilized Monomer Predicts Cellular Aggregation and Toxicity but Not In vitro Aggregation Propensity. Frontiers in Neuroscience 2016;10
    CrossRef
  13. Ivansson EL, Megquier K, Kozyrev SV, Murén E, Körberg IB, Swofford R, Koltookian M, Tonomura N, Zeng R, Kolicheski AL, Hansen L, Katz ML, Johnson GC, Johnson GS, Coates JR, Lindblad-Toh K. Variants within the SP110 nuclear body protein modify risk of canine degenerative myelopathy. Proceedings of the National Academy of Sciences 2016;113(22):E3091
    CrossRef
  14. Molina Recio G, García-Hernández L, Molina Luque R, Salas-Morera L. The role of interdisciplinary research team in the impact of health apps in health and computer science publications: a systematic review. BioMedical Engineering OnLine 2016;15(S1)
    CrossRef
  15. Doyle CM, Rumfeldt JA, Broom HR, Sekhar A, Kay LE, Meiering EM. Concurrent Increases and Decreases in Local Stability and Conformational Heterogeneity in Cu, Zn Superoxide Dismutase Variants Revealed by Temperature-Dependence of Amide Chemical Shifts. Biochemistry 2016;55(9):1346
    CrossRef
  16. Fujisawa T, Yamaguchi N, Kadowaki H, Tsukamoto Y, Tsuburaya N, Tsubota A, Takahashi H, Naguro I, Takahashi Y, Goto J, Tsuji S, Nishitoh H, Homma K, Ichijo H. A systematic immunoprecipitation approach reinforces the concept of common conformational alterations in amyotrophic lateral sclerosis-linked SOD1 mutants. Neurobiology of Disease 2015;82:478
    CrossRef
  17. Williams KL, McCann EP, Fifita JA, Zhang K, Duncan EL, Leo PJ, Marshall M, Rowe DB, Nicholson GA, Blair IP. Novel TBK1 truncating mutation in a familial amyotrophic lateral sclerosis patient of Chinese origin. Neurobiology of Aging 2015;36(12):3334.e1
    CrossRef
  18. Bourassa MW, Brown HH, Borchelt DR, Vogt S, Miller LM. Metal-deficient aggregates and diminished copper found in cells expressing SOD1 mutations that cause ALS. Frontiers in Aging Neuroscience 2014;6
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.2706)

:
  1. Molina-Recio G, García-Hernández L, Castilla-Melero A, Palomo-Romero JM, Molina-Luque R, Sánchez-Muñoz AA, Arauzo-Azofra A, Salas-Morera L. Bioinformatics and Biomedical Engineering. 2015. Chapter 3:24
    CrossRef