Publications by authors named "Nathaniel Pascual"
The widespread adoption of high-throughput omics technologies has exponentially increased the amount of protein sequence data involved in many salient disease pathways and their respective therapeutics and diagnostics. Despite the availability of large-scale sequence data, the lack of experimental fitness annotations underpins the need for self-supervised and unsupervised machine learning (ML) methods. These techniques leverage the meaningful features encoded in abundant unlabeled sequences to accomplish complex protein engineering tasks.
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- - The text discusses how single-cell RNA sequencing (scRNA-seq) can be used to profile immune cells, particularly focusing on designing monoclonal antibodies (mAbs).
- - It describes a process where scRNA-seq helps identify B-cell receptor sequences from immunized mice as a foundation for developing single-chain antibody fragments (scFabs) on yeast for efficient testing.
- - The method mentioned allows for integration with various in silico tools to enhance antibody properties like affinity, stability, solubility, and immunogenicity, although detailed explanations are not fully covered.
Extracellular vesicles (EVs) are naturally released, cell-derived vesicles that mediate intracellular communication, in part, by transferring genetic information and, thus, have the potential to be modified for use as a therapeutic gene or drug delivery vehicle. Advances in EV engineering suggest that directed delivery can be accomplished via surface alterations. Here we assess enriched delivery of engineered EVs displaying an organ targeting peptide specific to the pancreas.
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