D
Dennis P. Wall
Researcher at Stanford University
Publications - 187
Citations - 8592
Dennis P. Wall is an academic researcher from Stanford University. The author has contributed to research in topics: Autism & Autism spectrum disorder. The author has an hindex of 43, co-authored 158 publications receiving 6789 citations. Previous affiliations of Dennis P. Wall include Harvard University & Beth Israel Deaconess Medical Center.
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Journal ArticleDOI
Topic modeling for multi-omic integration in the human gut microbiome and implications for Autism
Christine A. Tataru,Marie Peras,Erica Rutherford,Kaiti Dunlap,Xiaochen Yin,Brianna Chrisman,Todd Z. DeSantis,Dennis P. Wall,Shoko Iwai,Maude M. David +9 more
TL;DR: This study applies Latent Dirichlet Allocation (LDA) to multi-omic microbial data from the stool of 81 children with and without Autism, and identifies topics, or microbial processes, that summarize complex phenomena occurring within gut microbial communities.
Posted ContentDOI
Transmission Dynamics of Human Herpesviruses and Other Blood DNA Viruses from Whole Genome Sequences of Families
Brianna Chrisman,Chloe He,Jae-Yoon Jung,Nate Tyler Stockham,Kelley Paskov,Peter Washington,Dennis P. Wall +6 more
TL;DR: In addition to extensively cataloguing the viruses detected in WGS of human whole blood and lymphoblastoid cell lines, the family structure of the dataset is used to show that household drives transmission of many microbes.
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A maximum flow-based network approach for identification of stable noncoding biomarkers associated with the multigenic neurological condition, autism.
Maya Varma,Kelley Paskov,Brianna Chrisman,Min Woo Sun,Jae-Yoon Jung,Nate Tyler Stockham,Peter Washington,Dennis P. Wall +7 more
TL;DR: In this paper, a graph-based methodology based on maximum flow is proposed to identify stable sets of variants associated with complex multigenic disorders, which can help pave the way towards biomarker-based diagnosis methods for complex genetic disorders.
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Optimizing a de novo artificial intelligence-based medical device under a predetermined change control plan: Improved ability to detect or rule out pediatric autism
TL;DR: In this article , the authors used the predetermined change control plan (PCCP) to improve the performance of a de novo autism diagnostic device in practice, using a repeated train/test validation procedure on a dataset of 722 children with concern for developmental delay.
Journal ArticleDOI
Statistical Learning Methods to Identify Nonwear Periods From Accelerometer Data
Sahej D Randhawa,Madalina Fiterau,Jorge A. Banda,Farish Haydel,Kristopher Kapphahn,Donna M. Matheson,Hyatt Moore,Robyn Ball,Clete A. Kushida,Scott L. Delp,Dennis P. Wall,Thomas N. Robinson,Manisha Desai +12 more
TL;DR: In this article , Hidden Markov Models (HMM) and Gaussian Mixture Models (GMM) were applied to classify states of nonwear and wear in triaxial acceleration data.