Author

L. Salichos

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Cancer Biology· 1 Cell Biology· 1 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Research Focus:protein folding & dynamics· 1 Assay:proteomics· 1 Approach:statistical model· 1 Research Focus:trajectory inference· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

M. Gerstein· 3 shared J. Warrell· 2 shared B. E. Turk· 1 shared C. Song· 1 shared G. Shi· 1 shared H. J. Lou· 1 shared J. Torres Robles· 1 shared M. Gancz· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 20 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersCell Biology

M. Gerstein

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Proteome-wide screening for mitogen-activated protein kinase docking motifs and interactors

G. Shi, J. Torres Robles, C. Song, L. Salichos, H. J. Lou, M. Gerstein, B. E. Turk

The paper screens for MAPK docking motifs and interactors using a yeast-based genetic pipeline, identifying novel sequences and residues critical for binding to JNK1 and p38.

bioRxiv · Aug 20, 2021Cell Biology

Latent Evolutionary Signatures: A General Framework for Analyzing Music and Cultural Evolution

J. Warrell, L. Salichos, M. Gancz, M. Gerstein

This paper introduces a framework to identify evolutionary processes in music by extracting latent signatures, showing improved performance in period and genre prediction.

bioRxiv · Oct 23, 2020 · PreprintEvolutionary Biology

Estimating growth patterns and driver effects in tumor evolution from individual samples

L. Salichos, W. U. Meyerson, J. Warrell, M. Gerstein

This paper develops a method to estimate tumor growth patterns and driver effects from individual whole genome sequencing data by analyzing variant allele frequencies.

bioRxiv · Sep 2, 2019Cancer Biology