User profiles for Georgina Stegmayer
 | Georgina StegmayerSinc(i)-CONICET Verified email at sinc.unl.edu.ar Cited by 1227 |
Predicting novel microRNA: a comprehensive comparison of machine learning approaches
Motivation The importance of microRNAs (miRNAs) is widely recognized in the community
nowadays because these short segments of RNA can play several roles in almost all …
nowadays because these short segments of RNA can play several roles in almost all …
Deep neural architectures for highly imbalanced data in bioinformatics
…, C Yones, DH Milone, G Stegmayer - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
In the postgenome era, many problems in bioinformatics have arisen due to the generation
of large amounts of imbalanced data. In particular, the computational classification of …
of large amounts of imbalanced data. In particular, the computational classification of …
Genome-wide discovery of pre-miRNAs: comparison of recent approaches based on machine learning
…, C Yones, DH Milone, G Stegmayer - Briefings in …, 2021 - academic.oup.com
Motivation The genome-wide discovery of microRNAs (miRNAs) involves identifying sequences
having the highest chance of being a novel miRNA precursor (pre-miRNA), within all the …
having the highest chance of being a novel miRNA precursor (pre-miRNA), within all the …
Automatic recognition of quarantine citrus diseases
G Stegmayer, DH Milone, S Garran, L Burdyn - Expert systems with …, 2013 - Elsevier
Citrus exports to foreign markets are severely limited today by fruit diseases. Some of them,
like citrus canker, black spot and scab, are quarantine for the markets. For this reason, it is …
like citrus canker, black spot and scab, are quarantine for the markets. For this reason, it is …
Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches
Motivation In contrast to messenger RNAs, the function of the wide range of existing long
noncoding RNAs (lncRNAs) largely depends on their structure, which determines interactions …
noncoding RNAs (lncRNAs) largely depends on their structure, which determines interactions …
Transfer learning in proteins: evaluating novel protein learned representations for bioinformatics tasks
A representation method is an algorithm that calculates numerical feature vectors for
samples in a dataset. Such vectors, also known as embeddings, define a relatively low-dimensional …
samples in a dataset. Such vectors, also known as embeddings, define a relatively low-dimensional …
A neural network model for estimating the particle size distribution of dilute latex from multiangle dynamic light scattering measurements
LM Gugliotta, GS Stegmayer… - Particle & Particle …, 2009 - Wiley Online Library
The particle size distribution (PSD) of dilute latex was estimated through a general regression
neural network (GRNN) that was supplied with PSD average diameters derived from …
neural network (GRNN) that was supplied with PSD average diameters derived from …
Novel SARS-CoV-2 encoded small RNAs in the passage to humans
Motivation The Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) has recently
emerged as the responsible for the pandemic outbreak of the coronavirus disease 2019. …
emerged as the responsible for the pandemic outbreak of the coronavirus disease 2019. …
Hierarchical deep learning for predicting GO annotations by integrating protein knowledge
Motivation Experimental testing and manual curation are the most precise ways for assigning
Gene Ontology (GO) terms describing protein functions. However, they are expensive, time-…
Gene Ontology (GO) terms describing protein functions. However, they are expensive, time-…
miRe2e: a full end-to-end deep model based on transformers for prediction of pre-miRNAs
Motivation MicroRNAs (miRNAs) are small RNA sequences with key roles in the regulation
of gene expression at post-transcriptional level in different species. Accurate prediction of …
of gene expression at post-transcriptional level in different species. Accurate prediction of …