Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data
ID Dinov - Gigascience, 2016 - academic.oup.com
Managing, processing and understanding big healthcare data is challenging, costly and
demanding. Without a robust fundamental theory for representation, analysis and inference …
demanding. Without a robust fundamental theory for representation, analysis and inference …
Machine learning and genome annotation: a match meant to be?
By its very nature, genomics produces large, high-dimensional datasets that are well suited
to analysis by machine learning approaches. Here, we explain some key aspects of …
to analysis by machine learning approaches. Here, we explain some key aspects of …
iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition
Motivation: Enhancers are of short regulatory DNA elements. They can be bound with
proteins (activators) to activate transcription of a gene, and hence play a critical role in …
proteins (activators) to activate transcription of a gene, and hence play a critical role in …
iEnhancer-EL: identifying enhancers and their strength with ensemble learning approach
B Liu, K Li, DS Huang, KC Chou - Bioinformatics, 2018 - academic.oup.com
Motivation Identification of enhancers and their strength is important because they play a
critical role in controlling gene expression. Although some bioinformatics tools were …
critical role in controlling gene expression. Although some bioinformatics tools were …
Introducing BASE: the Biomes of Australian Soil Environments soil microbial diversity database
Background Microbial inhabitants of soils are important to ecosystem and planetary
functions, yet there are large gaps in our knowledge of their diversity and ecology. The …
functions, yet there are large gaps in our knowledge of their diversity and ecology. The …
Enhancers and super-enhancers have an equivalent regulatory role in embryonic stem cells through regulation of single or multiple genes
SD Moorthy, S Davidson, VM Shchuka… - Genome …, 2017 - genome.cshlp.org
Transcriptional enhancers are critical for maintaining cell-type–specific gene expression and
driving cell fate changes during development. Highly transcribed genes are often associated …
driving cell fate changes during development. Highly transcribed genes are often associated …
iEnhancer-XG: interpretable sequence-based enhancers and their strength predictor
Motivation Enhancers are non-coding DNA fragments with high position variability and free
scattering. They play an important role in controlling gene expression. As machine learning …
scattering. They play an important role in controlling gene expression. As machine learning …
RFECS: a random-forest based algorithm for enhancer identification from chromatin state
Transcriptional enhancers play critical roles in regulation of gene expression, but their
identification in the eukaryotic genome has been challenging. Recently, it was shown that …
identification in the eukaryotic genome has been challenging. Recently, it was shown that …
BiRen: predicting enhancers with a deep-learning-based model using the DNA sequence alone
Motivation Enhancer elements are noncoding stretches of DNA that play key roles in
controlling gene expression programmes. Despite major efforts to develop accurate …
controlling gene expression programmes. Despite major efforts to develop accurate …
Integrative machine learning framework for the identification of cell-specific enhancers from the human genome
Enhancers are deoxyribonucleic acid (DNA) fragments which when bound by transcription
factors enhance the transcription of related genes. Due to its sporadic distribution and …
factors enhance the transcription of related genes. Due to its sporadic distribution and …