Contig: Self-supervised multimodal contrastive learning for medical imaging with genetics
High annotation costs are a substantial bottleneck in applying modern deep learning
architectures to clinically relevant medical use cases, substantiating the need for novel …
architectures to clinically relevant medical use cases, substantiating the need for novel …
Association of leaf spectral variation with functional genetic variants
The application of in-field and aerial spectroscopy to assess functional and phylogenetic
variation in plants has led to novel ecological insights and promises to support global …
variation in plants has led to novel ecological insights and promises to support global …
Pseudotime analysis for time-series single-cell sequencing and imaging data
Many single-cell RNA-sequencing studies have collected time-series data to investigate
transcriptional changes with respect to various notions of biological time, such as cell …
transcriptional changes with respect to various notions of biological time, such as cell …
A scoping review and bibliometric analysis (ScoRBA) of machine learning in genetic data analysis: unveiling the transformative potential
WNA Zakaria, H Zahiruddin, ZA Zukarnain… - Rwanda Medical …, 2024 - ajol.info
This study uses scoping review and bibliometric analysis; ScoRBA, to comprehensively
highlight the recurrent themes linked to machine learning (ML) applications in genetic data …
highlight the recurrent themes linked to machine learning (ML) applications in genetic data …
Detection of Genetic Disorders Using Ensemble Machine Learning Techniques: An Exploratory Study on the Identification of Genetic Abnormalities Through Advanced …
B Jamil, SS Rima, K Biswas, PK Ghosh - Doctoral Symposium on …, 2024 - Springer
Genetic disorders arise from alterations in DNA sequences, presenting complex structures
and diverse symptomatology that necessitate the use of sophisticated algorithmic …
and diverse symptomatology that necessitate the use of sophisticated algorithmic …
Use of Machine Learning for the Optimization of Genetic Circuits in Synthetic Biology: Focusing On Promoter Prediction for Gene Expression in Escherichia Coli
NC Ineza - 2024 - air.ashesi.edu.gh
This study explores the application of Machine Learning (ML) in optimizing genetic circuit
design in Synthetic Biology, particularly focusing on predicting specific promoter for gene …
design in Synthetic Biology, particularly focusing on predicting specific promoter for gene …
Detection of Genetic Disorders Using Ensemble Machine Learning Techniques: An Exploratory Study
B Jamil, SS Rima, K Biswas - Proceedings of Fifth Doctoral Symposium … - books.google.com
Genetic disorders arise from alterations in DNA sequences, presenting complex structures
and diverse symptomatology that necessitate the use of sophis-ticated algorithmic …
and diverse symptomatology that necessitate the use of sophis-ticated algorithmic …
Classification of human coding and non-coding regions based on CNN architecture
FB Nasr, AE Oueslati - 2022 IEEE Information Technologies & …, 2022 - ieeexplore.ieee.org
Studying role and properties related to DNA sequences is a very difficult task. This task is
more difficult when it comes to human genome which is composed by coding and non …
more difficult when it comes to human genome which is composed by coding and non …