Chamorro Parejo, Andrés David

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Albertlast: A bidirectional encoder representation of a transformer's approach for the estimation of Line-1 content
(2023-05-12) Chamorro Parejo, Andrés David; Seguel Campodónico, Juan Jaime; College of Engineering; Ramos, Kenneth; Schütz Schmuck, Marko; Rivera Gallego, Wilson; Arzuaga Cruz, Emmanuel; Department of Computer Science and Engineering; Rodrı́guez Román, Daniel
Technological breakthroughs in high-throughput sequencing platforms have triggered a revolution in genomics. This revolution has significantly augmented an already large number of genomic datasets, and their sizes. Every increase in the amount of data brings about challenges to the ability to process it. For certain bioinformatics tasks, it is no longer possible, or desirable, to rely exclusively on classical alignment and mapping methods. This is, for example, the case of methods for the identification of LINE-1 in the genome, which present challenges in accurately identifying the variations associated with the inserts in a sample. This dissertation developed a masking model using the Bidirectional Encoder Representations from Transformers (BERT) technique and used it to develop a transformer classification model. The final product is an innovative alignment-free system that detect and analyze polymorphic LINE-1 insertions and content estimation in a sample.