Alon Shaiber
Associate Director, Computational Biology
City of White Plains, New York, United States
Summary
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Senior🎓
Top SchoolAlon Shaiber is an Associate Director of Computational Biology with a decade of experience applying genomics and data science to accelerate therapeutics development and precision oncology. He moved from studying structural variation in cancer genomes at Weill Cornell and the New York Genome Center to leading computational biology teams at Immunai, where he now partners with pharma to translate single-cell and omics insights into drug discovery. Trained as a physicist and a PhD in biophysics, he blends rigorous algorithm development and scalable workflow engineering—evident from his doctoral work automating metagenome analyses and contributions to the widely used anvi’o platform’s backend database for gene detection. Comfortable bridging academia, industry, and cross-functional teams, he thrives on collaborative problem solving and building tools that make complex genomic signals actionable for patient care.
10 years of coding experience
9 years of employment as a software developer
Bachelor of Science (B.Sc.) Physics; Mathematics, Bachelor of Science (B.Sc.) Physics; Mathematics at The Hebrew University of JerusalemDoctor of Philosophy (Ph.D.) Biophysics, Doctor of Philosophy (Ph.D.) Biophysics at University of Chicago
Stackoverflow
31reputation
1kreached
0answers
1question
Github Skills (7)
bioinformatics10
biom10
python10
database-design10
data-processing10
pandas9
snakemake6
Programming languages (10)
Github contributions (5)
merenlab/anvio
Feb 2017 - Jan 2022
An analysis and visualization platform for 'omics data
Role in this project:
Back-end Developer
Back-end DeveloperContributions:985 commits, 69 PRs, 636 pushes in 5 years
Contributions summary:Alon contributed significantly to the development of the anvio bioinformatics platform by adding and modifying features related to gene detection and associated database operations. Their work included the creation of new tables and classes within the core database functionalities of the project, specifically to handle and store gene detection data at the gene level. They implemented methods for analyzing contigs to determine gene detection values and methods for data storage and merging, indicating a focus on the database infrastructure for handling omics data. Furthermore, they updated the color schemes for gene classes.
visualizationmetagenomicsmetatranscriptomicspangenomicscomparative-genomics
merenlab/MerenLab-workflows
Jun 2017 - Jan 2018
A repository with scripts to run pipeline that are commonly used in the Meren Lab
Contributions:172 commits, 5 PRs, 87 pushes in 7 months
commonlylabpipelineworkflow
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