Philip John Freda

Philip John Freda
Cedars-Sinai Medical Center

Doctor of Philosophy
Development of AI algorithms for the analysis of complex traits including the development of opioid use disorder (OUD)

About

18
Publications
32,580
Reads
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140
Citations
Introduction
I am a postdoctoral scientist investigating the basis of complex traits using AI at Cedars-Sinai Medical Center. I am broadly interested in the genetic and environmental features of complex traits in many systems including Drosophila, mice, and humans using machine learning and artificial intelligence. My interests range from opioid addiction and surgical success in humans to a host of phenotypes in model systems
Additional affiliations
January 2022 - present
Cedars-Sinai Medical Center
Position
  • Postdoctoral Scientist
Description
  • Research in complex traits in humans, mice, and Drosophila focusing using artificial intelligence and machine learning.
May 2019 - January 2022
University of Pennsylvania
Position
  • PostDoc Position
Description
  • Research in the risk assessment of the development of opioid use disorder (OUD)
August 2016 - December 2016
Kansas State University
Position
  • Lecturer
Description
  • Creation and instruction of lectures focusing on the relationships between insects and humans. Lectured on insect biology, evolution, taxonomy, behavior, and ecology. Grading of exams, essays, and quizzes
Education
August 2014 - December 2018
Kansas State University
Field of study
  • Entomology
August 2012 - May 2014
August 2001 - December 2005
Pennsylvania State University
Field of study
  • Administration of Justice, Minor in Sociology

Publications

Publications (18)
Article
As organisms age the environment fluctuates, exerting differential selection across ontogeny. In particular, highly seasonal environments expose life stages to often drastically different thermal environments. This developmental variation is particularly striking in organisms with complex life cycles, wherein life history stages also exhibit distin...
Article
Overall, our results provide substantial evidence that thermal hardiness and developmental acclimation responses are decoupled across metamorphosis in D. melanogaster. We do provide evidence that environmental variation can substantially alter genetic correlations among traits (heat hardiness and cold hardiness), but not genetic correlations across...
Article
Opioid use disorder (OUD) creates significant public health and economic burdens worldwide. Therefore, understanding the risk factors that lead to the development of OUD is fundamental to reducing both its prevalence and its impact. Significant sources of OUD risk include co-occurring lifetime and current diagnoses of both psychiatric disorders, pr...
Article
Organisms with complex life cycles demonstrate a remarkable ability to change their phenotypes across development, presumably as an evolutionary adaptation to developmentally variable environments. Developmental variation in environmentally sensitive performance, and thermal sensitivity in particular, has been well documented in holometabolous inse...
Article
Full-text available
Background Opioid use disorder (OUD) is underdiagnosed in health system settings, limiting research on OUD using electronic health records (EHRs). Medical encounter notes can enrich structured EHR data with documented signs and symptoms of OUD and social risks and behaviors. To capture this information at scale, natural language processing (NLP) to...
Preprint
Organisms with complex life cycles demonstrate a remarkable ability to change their phenotypes across development, presumably as an evolutionary adaptation to developmentally variable environments. Developmental variation in environmentally sensitive performance, and thermal sensitivity in particular, has been well documented in holometabolous inse...
Article
Environmental challenges presented by temperature variation can be overcome through phenotypic plasticity in small invasive ectotherms. We tested the effect of thermal exposure to 21, 18, and 11°C throughout the whole life cycle of individuals, thermal exposure of adults reared at 25°C to 15 and 11°C for a 21-d period, and long (14:10 hr) and short...
Poster
The adaptive decoupling hypothesis - complex life cycles evolve to genetically separate life stages, allowing stage-specific responses to selective forces. Insects that undergo complete metamorphosis are often subject to distinct thermal habitats, resulting in differential selection across development. We test for genetic decoupling in thermal hard...
Presentation
Full-text available
A presentation explaining how and why larvae and adults may reach distinct fitness optima due to a genetic decoupling of thermal stress responses. Takes about possibly differences in RNAseq profiles
Presentation
Full-text available
Does decoupled physiology via a complex life cycle lead to a decoupled stress response and potential evolutionary independence across metamorphosis? This presentation points to yes!
Presentation
Full-text available
Showing data of phenotypic correlation for cold hardiness between larvae and adults of Drosophila melanogaster. There are 139 line used in this study. There are also manhattan plots showing SNPs that are in association with variation in cold hardiness in each life stage. From a 3 minute thesis competition
Presentation
Full-text available
Presentation at SICB 2016 discussing my findings of a complete phenotype and quantitative genetic decoupling of thermal hardiness across metamorphosis in Drosophila melanogaster
Presentation
Full-text available
A proposal talk discussing the possibility and implications of complete genetic decoupling of stress traits across metamorphosis with preliminary results.
Poster
Full-text available
Poster showing the decoupling of cold hardiness across metamorphosis at both a phenotypic and quantitative level in Drosophila melanogaster
Presentation
Full-text available
A presentation talking about two main points: 1.) If complex life cycles evolved to decouple life stages, does the underlying genetic architecture associated with a trait change across ontogeny? If so, to what degree? and 2.) What are the physiological mechanisms facilitating observed changes?
Article
Full-text available
The Muller F element (4.2 Mb, ~80 protein-coding genes) is an unusual autosome of Drosophila melanogaster; it is mostly heterochromatic with a low recombination rate. To investigate how these properties impact the evolution of repeats and genes, we manually improved the sequence and annotated the genes on the D. erecta, D. mojavensis, and D. grimsh...
Article
Full-text available
A good Drosophila trap should be made of materials that are inexpensive and readily available. Also, the materials should be sturdy enough to be used outdoors. Additionally, a trap should be simple enough that anyone can assemble it quickly. The trap of Medeiros and Klaczko (1999) is well designed, but improvements and simplifications are possible....
Article
Full-text available
Collections of Drosophila and their relatives were performed using bait traps on the campus of Saint Joseph's University, in Philadelphia and Lower Merion, Pennsylvania, between July and December 2011 and continuing in March of 2012. In the 2011 collection season, more than 200 specimens of Drosophila suzukii (Matsumura), or spotted wing Drosophila...

Questions

Questions (2)
Question
I have sets of FlyBase gene ID's that I would like to perform KEGG Pathway analysis on but the KAAS (http://www.genome.jp/kaas-bin/kaas_main) seems to require sequence data to perform BLAST with. Is there a way that I can just submit my gene ID's and perform the analysis that way?
Question
I have been working with a QTL dataset for quite some time and keep stumbling over an issue. Out of the 1000 or so markers I have, a number of them have the same location value (in cM) as other markers. 
In other words:
marker x: 10.05 cM
marker y: 10.05 cM
marker z: 10.05 cM
First, I removed all of the markers that had some type of overlap associated, leaving only one that was associated with some physical gene or bp location. This limited my dataset to approximately 215 markers, a far cry from my original 1000.
I got the results and then tried it again with the original 1000 markers. I am using QTL Cartographer (Unix) v. 1.17 for the analysis. Interestingly, during the analysis in both LRmapqtl and SRmapqtl, I noticed strange output within the terminal like "cond.denom=0" over and over again. I am guessing this is occurring because the recombinational distances between some markers is 0 and therefore are being excluded. However, the output from the 1000 marker analysis yielded more QTL with higher resolution with peaks being in the same general locations as the 215 marker analysis (some just became significant in the 1000 marker analysis)
Should I remove the markers and stick with the ~215 that do not overlap?
Will my data be erroneous if I leave the other ~800 or so markers in?
Any help would be appreciated.

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Projects

Projects (2)
Project
Using machine learning and artificial intelligence to both predict and identify risk factors of problematic opioid use.
Project
Test the adaptive decoupling hypothesis using genomics and transcriptomics in a model system.