Format
Sort by
Items per page

Send to

Choose Destination

Search results

Items: 1 to 50 of 88

1.

Identification and Quantification of Gaps in Access to Autism Resources in the United States: An Infodemiological Study.

Ning M, Daniels J, Schwartz J, Dunlap K, Washington P, Kalantarian H, Du M, Wall DP.

J Med Internet Res. 2019 Jul 10;21(7):e13094. doi: 10.2196/13094.

PMID:
31293243
Free Article
2.

Addendum to the Acknowledgements: Validity of Online Screening for Autism: Crowdsourcing Study Comparing Paid and Unpaid Diagnostic Tasks.

Washington P, Kalantarian H, Tariq Q, Schwartz J, Dunlap K, Chrisman B, Varma M, Ning M, Kline A, Stockham N, Paskov K, Voss C, Haber N, Wall DP.

J Med Internet Res. 2019 Jun 27;21(6):e14950. doi: 10.2196/14950.

3.

Validity of Online Screening for Autism: Crowdsourcing Study Comparing Paid and Unpaid Diagnostic Tasks.

Washington P, Kalantarian H, Tariq Q, Schwartz J, Dunlap K, Chrisman B, Varma M, Ning M, Kline A, Stockham N, Paskov K, Voss C, Haber N, Wall DP.

J Med Internet Res. 2019 May 23;21(5):e13668. doi: 10.2196/13668. Erratum in: J Med Internet Res. 2019 Jun 27;21(6):e14950.

4.

Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study.

Tariq Q, Fleming SL, Schwartz JN, Dunlap K, Corbin C, Washington P, Kalantarian H, Khan NZ, Darmstadt GL, Wall DP.

J Med Internet Res. 2019 Apr 24;21(4):e13822. doi: 10.2196/13822.

5.

Effect of Wearable Digital Intervention for Improving Socialization in Children With Autism Spectrum Disorder: A Randomized Clinical Trial.

Voss C, Schwartz J, Daniels J, Kline A, Haber N, Washington P, Tariq Q, Robinson TN, Desai M, Phillips JM, Feinstein C, Winograd T, Wall DP.

JAMA Pediatr. 2019 Mar 25. doi: 10.1001/jamapediatrics.2019.0285. [Epub ahead of print]

6.

Coalitional Game Theory Facilitates Identification of Non-Coding Variants Associated With Autism.

Sun MW, Gupta A, Varma M, Paskov KM, Jung JY, Stockham NT, Wall DP.

Biomed Inform Insights. 2019 Mar 8;11:1178222619832859. doi: 10.1177/1178222619832859. eCollection 2019.

7.

Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder.

Varma M, Paskov KM, Jung JY, Sierra Chrisman B, Stockham NT, Washington PY, Wall DP.

Pac Symp Biocomput. 2019;24:260-271.

8.

Mobile detection of autism through machine learning on home video: A development and prospective validation study.

Tariq Q, Daniels J, Schwartz JN, Washington P, Kalantarian H, Wall DP.

PLoS Med. 2018 Nov 27;15(11):e1002705. doi: 10.1371/journal.pmed.1002705. eCollection 2018 Nov.

9.

A Low Rank Model for Phenotype Imputation in Autism Spectrum Disorder.

Paskov KM, Wall DP.

AMIA Jt Summits Transl Sci Proc. 2018 May 18;2017:178-187. eCollection 2018.

10.

Machine learning approach for early detection of autism by combining questionnaire and home video screening.

Abbas H, Garberson F, Glover E, Wall DP.

J Am Med Inform Assoc. 2018 Aug 1;25(8):1000-1007. doi: 10.1093/jamia/ocy039.

PMID:
29741630
11.

Brain-specific functional relationship networks inform autism spectrum disorder gene prediction.

Duda M, Zhang H, Li HD, Wall DP, Burmeister M, Guan Y.

Transl Psychiatry. 2018 Mar 6;8(1):56. doi: 10.1038/s41398-018-0098-6.

12.

Feasibility Testing of a Wearable Behavioral Aid for Social Learning in Children with Autism.

Daniels J, Haber N, Voss C, Schwartz J, Tamura S, Fazel A, Kline A, Washington P, Phillips J, Winograd T, Feinstein C, Wall DP.

Appl Clin Inform. 2018 Jan;9(1):129-140. doi: 10.1055/s-0038-1626727. Epub 2018 Feb 21.

13.

Sparsifying machine learning models identify stable subsets of predictive features for behavioral detection of autism.

Levy S, Duda M, Haber N, Wall DP.

Mol Autism. 2017 Dec 19;8:65. doi: 10.1186/s13229-017-0180-6. eCollection 2017.

14.

Coalitional game theory as a promising approach to identify candidate autism genes.

Gupta A, Sun MW, Paskov KM, Stockham NT, Jung JY, Wall DP.

Pac Symp Biocomput. 2018;23:436-447.

15.

The GapMap project: a mobile surveillance system to map diagnosed autism cases and gaps in autism services globally.

Daniels J, Schwartz J, Albert N, Du M, Wall DP.

Mol Autism. 2017 Oct 23;8:55. doi: 10.1186/s13229-017-0163-7. eCollection 2017.

16.

Human Genome Sequencing at the Population Scale: A Primer on High-Throughput DNA Sequencing and Analysis.

Goldfeder RL, Wall DP, Khoury MJ, Ioannidis JPA, Ashley EA.

Am J Epidemiol. 2017 Oct 15;186(8):1000-1009. doi: 10.1093/aje/kww224. Review.

17.

Crowdsourced validation of a machine-learning classification system for autism and ADHD.

Duda M, Haber N, Daniels J, Wall DP.

Transl Psychiatry. 2017 May 16;7(5):e1133. doi: 10.1038/tp.2017.86.

18.

GapMap: Enabling Comprehensive Autism Resource Epidemiology.

Albert N, Daniels J, Schwartz J, Du M, Wall DP.

JMIR Public Health Surveill. 2017 May 4;3(2):e27. doi: 10.2196/publichealth.7150.

19.

Cross-disorder comparative analysis of comorbid conditions reveals novel autism candidate genes.

Diaz-Beltran L, Esteban FJ, Varma M, Ortuzk A, David M, Wall DP.

BMC Genomics. 2017 Apr 20;18(1):315. doi: 10.1186/s12864-017-3667-9.

20.

Refining the role of de novo protein-truncating variants in neurodevelopmental disorders by using population reference samples.

Kosmicki JA, Samocha KE, Howrigan DP, Sanders SJ, Slowikowski K, Lek M, Karczewski KJ, Cutler DJ, Devlin B, Roeder K, Buxbaum JD, Neale BM, MacArthur DG, Wall DP, Robinson EB, Daly MJ.

Nat Genet. 2017 Apr;49(4):504-510. doi: 10.1038/ng.3789. Epub 2017 Feb 13.

21.

MC-GenomeKey: a multicloud system for the detection and annotation of genomic variants.

Elshazly H, Souilmi Y, Tonellato PJ, Wall DP, Abouelhoda M.

BMC Bioinformatics. 2017 Jan 20;18(1):49. doi: 10.1186/s12859-016-1454-2.

22.

DE NOVO MUTATIONS IN AUTISM IMPLICATE THE SYNAPTIC ELIMINATION NETWORK.

Ram Venkataraman G, O'Connell C, Egawa F, Kashef-Haghighi D, Wall DP.

Pac Symp Biocomput. 2017;22:521-532. doi: 10.1142/9789813207813_0048.

23.

The Quantified Brain: A Framework for Mobile Device-Based Assessment of Behavior and Neurological Function.

Stark DE, Kumar RB, Longhurst CA, Wall DP.

Appl Clin Inform. 2016 May 4;7(2):290-8. doi: 10.4338/ACI-2015-12-LE-0176. eCollection 2016. No abstract available.

24.

Comorbid Analysis of Genes Associated with Autism Spectrum Disorders Reveals Differential Evolutionary Constraints.

David MM, Enard D, Ozturk A, Daniels J, Jung JY, Diaz-Beltran L, Wall DP.

PLoS One. 2016 Jul 14;11(7):e0157937. doi: 10.1371/journal.pone.0157937. eCollection 2016.

25.

Bioaccumulation of metals in ryegrass (Lolium perenne L.) following the application of lime stabilised, thermally dried and anaerobically digested sewage sludge.

Healy MG, Ryan PC, Fenton O, Peyton DP, Wall DP, Morrison L.

Ecotoxicol Environ Saf. 2016 Aug;130:303-9. doi: 10.1016/j.ecoenv.2016.04.026. Epub 2016 May 9.

PMID:
27174047
26.

A research roadmap for next-generation sequencing informatics.

Altman RB, Prabhu S, Sidow A, Zook JM, Goldfeder R, Litwack D, Ashley E, Asimenos G, Bustamante CD, Donigan K, Giacomini KM, Johansen E, Khuri N, Lee E, Liang XS, Salit M, Serang O, Tezak Z, Wall DP, Mansfield E, Kass-Hout T.

Sci Transl Med. 2016 Apr 20;8(335):335ps10. doi: 10.1126/scitranslmed.aaf7314. Review.

27.

Automated integration of continuous glucose monitor data in the electronic health record using consumer technology.

Kumar RB, Goren ND, Stark DE, Wall DP, Longhurst CA.

J Am Med Inform Assoc. 2016 May;23(3):532-7. doi: 10.1093/jamia/ocv206. Epub 2016 Mar 27.

28.

Identification of Human Neuronal Protein Complexes Reveals Biochemical Activities and Convergent Mechanisms of Action in Autism Spectrum Disorders.

Li J, Ma Z, Shi M, Malty RH, Aoki H, Minic Z, Phanse S, Jin K, Wall DP, Zhang Z, Urban AE, Hallmayer J, Babu M, Snyder M.

Cell Syst. 2015 Nov 25;1(5):361-374.

29.

Clinical Evaluation of a Novel and Mobile Autism Risk Assessment.

Duda M, Daniels J, Wall DP.

J Autism Dev Disord. 2016 Jun;46(6):1953-1961. doi: 10.1007/s10803-016-2718-4.

30.

Use of machine learning for behavioral distinction of autism and ADHD.

Duda M, Ma R, Haber N, Wall DP.

Transl Psychiatry. 2016 Feb 9;6:e732. doi: 10.1038/tp.2015.221.

31.

A common molecular signature in ASD gene expression: following Root 66 to autism.

Diaz-Beltran L, Esteban FJ, Wall DP.

Transl Psychiatry. 2016 Jan 5;6:e705. doi: 10.1038/tp.2015.112. Review.

32.

Scalable and cost-effective NGS genotyping in the cloud.

Souilmi Y, Lancaster AK, Jung JY, Rizzo E, Hawkins JB, Powles R, Amzazi S, Ghazal H, Tonellato PJ, Wall DP.

BMC Med Genomics. 2015 Oct 15;8:64. doi: 10.1186/s12920-015-0134-9.

33.

Identifying contrasting influences and surface water signals for specific groundwater phosphorus vulnerability.

Mellander PE, Jordan P, Shore M, McDonald NT, Wall DP, Shortle G, Daly K.

Sci Total Environ. 2016 Jan 15;541:292-302. doi: 10.1016/j.scitotenv.2015.09.082. Epub 2015 Sep 25.

PMID:
26410704
34.
35.

A transgenic resource for conditional competitive inhibition of conserved Drosophila microRNAs.

Fulga TA, McNeill EM, Binari R, Yelick J, Blanche A, Booker M, Steinkraus BR, Schnall-Levin M, Zhao Y, DeLuca T, Bejarano F, Han Z, Lai EC, Wall DP, Perrimon N, Van Vactor D.

Nat Commun. 2015 Jun 17;6:7279. doi: 10.1038/ncomms8279.

36.

Testing the accuracy of an observation-based classifier for rapid detection of autism risk.

Duda M, Kosmicki JA, Wall DP.

Transl Psychiatry. 2015 Apr 28;5:e556. doi: 10.1038/tp.2015.51. No abstract available.

37.

Searching for a minimal set of behaviors for autism detection through feature selection-based machine learning.

Kosmicki JA, Sochat V, Duda M, Wall DP.

Transl Psychiatry. 2015 Feb 24;5:e514. doi: 10.1038/tp.2015.7.

38.

Translational Meta-analytical Methods to Localize the Regulatory Patterns of Neurological Disorders in the Human Brain.

Sochat V, David M, Wall DP.

AMIA Annu Symp Proc. 2015 Nov 5;2015:2073-82. eCollection 2015.

39.

Testing the accuracy of an observation-based classifier for rapid detection of autism risk.

Duda M, Kosmicki JA, Wall DP.

Transl Psychiatry. 2014 Aug 12;4:e424. doi: 10.1038/tp.2014.65. Erratum in: Transl Psychiatry. 2014;4:e440.

40.

A framework for the interpretation of de novo mutation in human disease.

Samocha KE, Robinson EB, Sanders SJ, Stevens C, Sabo A, McGrath LM, Kosmicki JA, Rehnström K, Mallick S, Kirby A, Wall DP, MacArthur DG, Gabriel SB, DePristo M, Purcell SM, Palotie A, Boerwinkle E, Buxbaum JD, Cook EH Jr, Gibbs RA, Schellenberg GD, Sutcliffe JS, Devlin B, Roeder K, Neale BM, Daly MJ.

Nat Genet. 2014 Sep;46(9):944-50. doi: 10.1038/ng.3050. Epub 2014 Aug 3.

41.

COSMOS: Python library for massively parallel workflows.

Gafni E, Luquette LJ, Lancaster AK, Hawkins JB, Jung JY, Souilmi Y, Wall DP, Tonellato PJ.

Bioinformatics. 2014 Oct 15;30(20):2956-8. doi: 10.1093/bioinformatics/btu385. Epub 2014 Jun 30.

42.

Evaluating the critical source area concept of phosphorus loss from soils to water-bodies in agricultural catchments.

Shore M, Jordan P, Mellander PE, Kelly-Quinn M, Wall DP, Murphy PN, Melland AR.

Sci Total Environ. 2014 Aug 15;490:405-15. doi: 10.1016/j.scitotenv.2014.04.122. Epub 2014 May 24.

PMID:
24863139
43.

The potential of accelerating early detection of autism through content analysis of YouTube videos.

Fusaro VA, Daniels J, Duda M, DeLuca TF, D'Angelo O, Tamburello J, Maniscalco J, Wall DP.

PLoS One. 2014 Apr 16;9(4):e93533. doi: 10.1371/journal.pone.0093533. eCollection 2014.

44.

Genetic Networks of Complex Disorders: from a Novel Search Engine for PubMed Article Database.

Jung JY, Wall DP.

AMIA Jt Summits Transl Sci Proc. 2013 Mar 18;2013:99. eCollection 2013.

PMID:
24303309
45.

A literature search tool for intelligent extraction of disease-associated genes.

Jung JY, DeLuca TF, Nelson TH, Wall DP.

J Am Med Inform Assoc. 2014 May-Jun;21(3):399-405. doi: 10.1136/amiajnl-2012-001563. Epub 2013 Sep 2.

46.

Systems biology as a comparative approach to understand complex gene expression in neurological diseases.

Diaz-Beltran L, Cano C, Wall DP, Esteban FJ.

Behav Sci (Basel). 2013 May 21;3(2):253-72. doi: 10.3390/bs3020253. eCollection 2013 Jun. Review.

47.

Haplotype structure enables prioritization of common markers and candidate genes in autism spectrum disorder.

Vardarajan BN, Eran A, Jung JY, Kunkel LM, Wall DP.

Transl Psychiatry. 2013 May 28;3:e262. doi: 10.1038/tp.2013.38.

48.

Quantification of phosphorus transport from a karstic agricultural watershed to emerging spring water.

Mellander PE, Jordan P, Melland AR, Murphy PN, Wall DP, Mechan S, Meehan R, Kelly C, Shine O, Shortle G.

Environ Sci Technol. 2013 Jun 18;47(12):6111-9. doi: 10.1021/es304909y. Epub 2013 May 28.

PMID:
23672730
49.

Personalized cloud-based bioinformatics services for research and education: use cases and the elasticHPC package.

El-Kalioby M, Abouelhoda M, Krüger J, Giegerich R, Sczyrba A, Wall DP, Tonellato P.

BMC Bioinformatics. 2012;13 Suppl 17:S22. doi: 10.1186/1471-2105-13-S17-S22. Epub 2012 Dec 13.

50.

Autworks: a cross-disease network biology application for Autism and related disorders.

Nelson TH, Jung JY, Deluca TF, Hinebaugh BK, St Gabriel KC, Wall DP.

BMC Med Genomics. 2012 Nov 28;5:56. doi: 10.1186/1755-8794-5-56.

Supplemental Content

Support Center