Resume of Alex Amlie-Wolf, PhD

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Highly collaborative computational biologist with 13 years of experience in genomics and transcriptomics, large-scale data integration, RNA biology, and human genetics. 5+ years of industrial target nomination and drug development experience in disease areas including neuroscience, repeat expansions, immunology, and oncology. Experienced in people management, cross-functional collaboration, and communication with a wide range of audiences. Passionate about developing and applying computational methods to derive actionable biological insights from complex datasets.

Technical Skills

Programming: R (tidyverse, Rshiny), Python (large-scale data processing and ML), Unix and bash, cloud computing (AWS, GCP), pipelining and reproducible research (Snakemake, Nextflow, Docker, Anaconda), Jupyter, github/bitbucket, Atlassian (Confluence, Jira), auto-documentation (Sphinx), databases (SQL)

Computational biology: genomics (WES/WGS), transcriptomics (RNA-seq, TSS/PolyA-seq), epigenomics (ChIP/CLIP-seq), long read sequencing (Nanopore), proteomics, integrative analysis of public (FANTOM5, DepMap, ENCODE, GTEx, UK Biobank) and proprietary datasets, differential expression and differential splicing analysis, network biology and pathway analysis (IPA, GSEA, WGCNA) with regulatory factor inference, knowledge graphs, ontologies, machine learning and statistics, RNA structure prediction

Genetics: GWAS, QTL mapping, post-GWAS analysis (colocalization, functional data integration), haplotype deconvolution, repeat expansion, RNA splicing, transcriptional regulation, noncoding elements

Drug development: GWAS, QTL mapping, post-GWAS analysis (colocalization, functional data integration), haplotype deconvolution, repeat expansion, RNA splicing, transcriptional regulation, noncoding elements

Professional Experience

Arrakis Therapeutics, Waltham, MA

Scientist II, Computational Biology. July 2021-Present

Cross-functional, matrixed collaboration with biology and chemistry teams along the drug discovery process for neurology/repeat expansion, oncology, immunology, and additional target indications. This includes target RNA characterization and computational biology leadership around development of reproducible sequencing-based assays for compound discovery and screening and mouse PK/PD
Supervised and mentored one co-op student (H1 2021) who then transitioned to a Senior Research Associate position as my direct report (2022-2024)
Broadened skillset to include analysis of long read sequencing, proteomics, and RNA structure prediction tools to support integrative subtarget nominations for RNA-targeting small molecules
Facilitated maturation of internal data systems including documentation of computational pipelines and processes and supporting development of a data lake
Incorporated human genetics data into target assessments along with continuously updating omics data sources to support platform approaches spanning multiple mRNA-centric mechanisms

Scientist, Computational Biology. June 2019-June 2021

Multiomic (RNA-seq, TSS-seq, ribo-seq) analysis including differential expression and splicing, pathway and regulatory factor analysis of leaderboard compounds to characterize on- and off-target effects in relation to expected MoA and supporting Go/NoGo decisions on several projects
Developed reproducible cloud-based pipelines in close collaboration with experimentalists for sequencing data types including RNA-seq, TSS-seq, RACE-seq, polyA-seq & ribo-seq
Data mining of large-scale consortium (ENCODE, FANTOM5, CCLE, DepMap, GTEx), literature, and internal omics and genetics datasets for novel target characterization and prioritization based on RNA features for internal target pipeline and Roche and Amgen collaboration projects
Point person for academic collaboration and software licenses for computational biology requirements around RNA splicing assessment and pathway analysis (Qiagen)

University of Pennsylvania, Philadelphia, PA

PhD Student in Genomics & Computational Biology. August 2013-May 2019

Thesis research in Li-San Wang’s lab involved integrative computational and experimental approaches for characterizing the regulatory mechanisms underlying noncoding genetic variation
Lead development of open-source INFERNO method for integrating hundreds of functional genomics datasets to INFER the molecular mechanisms of NOncoding genetic variants, with web server: http://inferno.lisanwanglab.org
Applied INFERNO to Alzheimer’s Disease where I uncovered novel lncRNA-mediated regulatory mechanisms and performed luciferase validation of enhancer activity
Applied INFERNO to a variety of phenotypes: neurodegenerative diseases (Parkinson’s, PSP, ALS, CBD, FTD), psychiatric traits (schizophrenia, ADHD), and 2,419 UK Biobank phenotypes to nominate regulatory mechanisms underlying disease
Implemented HiPPIE2 pipeline for Hi-C data analysis, from raw reads to high-resolution interacting sites, with functional annotation and identification of enhancer-promoter interactions
Throughout my thesis work, I gained experience in analyzing many types of ‘omics data including RNA-seq and pathway analysis, ChIP-seq, DNA-seq, ATAC-seq, and Hi-C. I also applied statistical genetics approaches including colocalization, haplotype deconvolution, and Bayesian QTL mapping
My collaborative nature led me to many projects inside and outside of my thesis lab, spanning fields including neurodegenerative diseases (with Jerry Schellenberg, Virginia Lee, John Trojanowski, Eddie Lee), epigenetics (with Shelley Berger), and health economics (with Zeke Emanuel)

Education and Honors

Publications

FILER: a framework for harmonizing and querying large-scale functional genomics knowledge Permalink

Kuksa PP, Leung YY, Gangadharan P, ..., Amlie-Wolf A, et al. FILER: a framework for harmonizing and querying large-scale functional genomics knowledge. NAR Genomics and Bioinformatics (2022). 10.1093/nargab/lqab123

Using INFERNO to Infer the Molecular Mechanisms Underlying Noncoding Genetic Associations Permalink

Amlie-Wolf A*, et al. Using INFERNO to Infer the Molecular Mechanisms Underlying Noncoding Genetic Associations. Methods in Molecular Biology: Functional Analysis of Long Non-Coding RNAs (2021). 10.1007/978-1-0716-1158-6_6

SparkINFERNO: a scalable high-throughput pipeline for inferring molecular mechanisms of non-coding genetic variants Permalink

Kuksa PP, Amlie-Wolf A, et al., Wang LS. SparkINFERNO: a scalable high-throughput pipeline for inferring molecular mechanisms of non-coding genetic variants. Bioinformatics (2020). 10.1093/bioinformatics/btaa246

An integrated multi-omics approach identifies epigenetic alterations associated with Alzheimer’s disease Permalink

Nativio R, ..., Amlie-Wolf A, ..., Berger S. An integrated multi-omics approach identifies epigenetic alterations associated with Alzheimer's disease. Nature Genetics (2020). 10.1038/s41588-020-0696-0

HIPPIE2: a method for fine-scale identification of physically interacting chromatin regions Permalink

Kuksa PP, Amlie-Wolf A*, Hwang YC*, ..., Wang LS. HIPPIE2: a method for fine-scale identification of physically interacting chromatin regions. NAR Genomics and Bioinformatics (2020). 10.1093/nargab/lqaa022

Loss of Nuclear TDP-43 Is Associated with Decondensation of LINE Retrotransposons Permalink

Liu EY, ..., Amlie-Wolf A, ..., Lee EB. Loss of Nuclear TDP-43 Is Associated with Decondensation of LINE Retrotransposons. Cell Reports (2019). 10.1016/j.celrep.2019.04.003

Activity of the poly(A) binding protein MSUT2 determines susceptibility to pathological tau in the mammalian brain Permalink

Wheeler JM, ..., Amlie-Wolf A, ..., Kraemer B. Activity of the poly(A) binding protein MSUT2 determines susceptibility to pathological tau in the mammalian brain. Science Translational Medicine (2019). 10.1126/scitranslmed.aao6545

Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing Permalink

Kunkle BW, ..., Amlie-Wolf A, ..., Schellenberg GD, Lambert JC, Pericak-Vance MA. Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nature Genetics (2019). 10.1038/s41588-019-0358-2

Inferring the Molecular Mechanisms of Noncoding Alzheimer’s Disease-Associated Genetic Variants Permalink

Amlie-Wolf A*, Tang M*, ..., Wang LS, Schellenberg GD. Inferring the Molecular Mechanisms of Noncoding Alzheimer's Disease-Associated Genetic Variants. Journal of Alzheimer's Disease (2019). 10.3233/jad-190568

DASHR 2.0: integrated database of human small non-coding RNA genes and mature products Permalink

Kuksa PP, Amlie-Wolf A, et al., Wang LS. DASHR 2.0: integrated database of human small non-coding RNA genes and mature products. Bioinformatics (2018). 10.1093/bioinformatics/bty709

Dysregulation of the epigenetic landscape of normal aging in Alzheimer’s disease Permalink

Nativio R, ..., Amlie-Wolf A, ..., Berger S. Dysregulation of the epigenetic landscape of normal aging in Alzheimer's disease. Nature Neuroscience (2018). 10.1038/s41593-018-0101-9

SPAR: small RNA-seq portal for analysis of sequencing experiments Permalink

Kuksa PP, Amlie-Wolf A, et al., Leung YY. SPAR: small RNA-seq portal for analysis of sequencing experiments. Nucleic Acids Research (2018). 10.1093/nar/gky330

INFERNO: INFERring the molecular mechanisms of NOncoding genetic variants Permalink

Amlie-Wolf A*, ..., Brown CD, Schellenberg GD, Wang LS. INFERNO: INFERring the molecular mechanisms of NOncoding genetic variants. Nucleic Acids Research (2018). 10.1093/nar/gky686

DASHR: database of small human noncoding RNAs Permalink

Leung YY, Kuksa PP, Amlie-Wolf A, et al. DASHR: database of small human noncoding RNAs. Nucleic Acids Research (2016). 10.1093/nar/gkv1188

Transcriptomic Changes Due to Cytoplasmic TDP-43 Expression Reveal Dysregulation of Histone Transcripts and Nuclear Chromatin Permalink

Amlie-Wolf A*, ..., Trojanowski JQ, Lee VM, Wang LS, Lee EB. Transcriptomic Changes Due to Cytoplasmic TDP-43 Expression Reveal Dysregulation of Histone Transcripts and Nuclear Chromatin. PLoS ONE (2015). 10.1371/journal.pone.0141836

Talks

Application of IPA for interpreting RNA-targeted small molecule treatment datasets

September 22, 2022

Talk at Qiagen IPA User Group Meeting 2022, Waltham, Massachusetts

Inferring the shared noncoding regulatory mechanisms underlying genetic susceptibility to Alzheimer’s and Parkinson’s Diseases

March 30, 2019

Talk at AD/PD 2019, the 14th International Conference on Alzheimer’s and Parkinson’s Diseases and related neurological disorders, Lisbon, Portugal

Alex Amlie-Wolf