Leonidas Salichos

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Leonidas Salichos, Ph.D., is a computational biologist. His research focuses on studying evolving systems, such as the spread of infectious diseases and cancer evolution. To address these questions, he works on developing and implementing novel tools and methods based on phylogenetics, machine learning, statistics, and deep learning.

Salichos has a strong background in evolutionary and computational biology. While earning his M.S. in Agricultural Engineering at the Agricultural University of Athens, he developed a method that maps viral outbreaks. While working towards his M.S. in Bioinformatics at Katholieke Universiteit Leuven, he continued working on viruses by genotyping HIV strains. He earned his Ph.D. from Vanderbilt University in 2014. For his Ph.D. thesis, he developed several computational tools, including machine learning metrics to measure the internode and phylogenetic tree certainty based on conflicting phylogenetic signals.

As a postdoctoral researcher at Yale University, he worked on developing algorithms that calculate the impact of driver mutations in cancer by estimating growth patterns using variant allele frequencies. He also worked on the identification of mutational patterns and signatures, tumor subclonal architecture, and expressional profiles in 2800 cancer tumors. Meanwhile, he is collaborating on the analysis and characterization of viral strains in Italy. As an Associate Research Scientist and Lab collaborator at Yale University, Salichos has been studying the epidemiology of COVID-19 in the U.S. and the detection of infectious diseases across human tissues using next-generation sequencing techniques. He joined New York Tech in 2021.

Recent Projects and Research

• Modeling the spread of infectious diseases
• Quantifying music and cultural evolution
• Studying microbial populations across human tissues
• Determining genomic regions that impact tumor progression and immunotherapy treatments

Selected Publications

• Warrell, J., Salichos L. and Gerstein. Latent Evolutionary Signatures: A General Framework for Analyzing Music and Cultural Evolution. bioRχiv (2020).
• Salichos, L., Meyerson, W., Warrell, J. and Gerstein, M. Estimating growth patterns and driver effects in tumor evolution from individual samples. Nature Communications 11, (2020).
• Kumar, S., Warrell, J., Li, S., McGillivray, P. D., Meyerson, W., Salichos L et al. Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences. Cell 180, 915–927.e16 (2020).
• Catia Sias, Salichos L, Daniele Lapa, Franca Del Nonno, Andrea Baiocchini, Maria Rosaria Capobianchi, Anna Rosa Garbuglia (2019) Alpha, Beta, gamma human PapillomaViruses (HPV) detection with a different set of primers in oropharyngeal swabs, anal and cervical samples. Virology Journal volume 16, Article number: 27
• Salichos L, A. Stamatakis and A. Rokas (2014) Novel information theory-based measures for quantifying incongruence among phylogenetic trees. Mol. Biol. Evol. 31(5):1261–71.
• Salichos L, Rokas A. (2013) Inferring ancient divergences requires genes with strong phylogenetic signals. Nature 497(7449):327–31.

Courses Taught at New York Tech

• BIOL 150 W11 Phage Bioinformatics
• BIOL 250 Biostatistics
• BIOL 350 Bioinformatics

Contact

• lsalicho@nyit.edu
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