A5102766055- RNA and protein synthesis mechanisms
- Genomics and Chromatin Dynamics
- Pluripotent Stem Cells Research
- Evolution and Genetic Dynamics
- Genomics and Phylogenetic Studies
- CRISPR and Genetic Engineering
- RNA Research and Splicing
- Gene Regulatory Network Analysis
- Protein Degradation and Inhibitors
- Advanced biosensing and bioanalysis techniques
- Machine Learning in Bioinformatics
- 3D Printing in Biomedical Research
- Online Learning and Analytics
Max Planck Institute for Molecular Genetics
2020-2023
King Abdullah University of Science and Technology
2014-2021
University of Patras
2010-2014
Controlling cell fate has great potential for regenerative medicine, drug discovery, and basic research. Although transcription factors are able to promote reprogramming transdifferentiation, methods based on their upregulation often show low efficiency. Small molecules that can facilitate conversion between types ameliorate this problem working through safe, rapid, reversible mechanisms. Here, we present DECCODE, an unbiased computational method identification of such transcriptional data....
Motivation: Single nucleotide polymorphisms (SNPs) are considered the most frequently occurring DNA sequence variations. Several computational methods have been proposed for classification of missense SNPs to neutral and disease associated. However, existing approaches fail select relevant features by choosing them arbitrarily without sufficient documentation. Moreover, they limited problem missing values, imbalance between learning datasets do not support their predictions with confidence...
This paper proposes the implementation of an adaptive and personalized e-Learning system which is based on open source software technologies. Adaptation personalization received very little coverage in e-learning platforms. An course should not be designed without matching students' teachers' needs objectives as closely possible, adapting during progression. The proposed offers profiling services for teacher student while at same time adapts educational content tools basis acquired user's profile.
Abstract Motivation Recombination is one of the essential genetic processes for sexually reproducing organisms, which can happen more frequently in some regions, called recombination hotspots. Although several factors, such as PRDM9 binding motifs, are known to be related hotspots, their contributions hotspots have not been quantified, and other determinants yet elucidated. Here, we propose a computational method, RHSNet, based on deep learning signal processing, identify quantify hotspot...
Drug combination therapy for treatment of cancers and other multifactorial diseases has the potential increasing therapeutic effect, while reducing likelihood drug resistance. In order to reduce time cost spent in comprehensive screens, methods are needed which can model additive effects possible combinations.We here show that transcriptional response combinatorial at promoters, as measured by single molecule CAGE technology, is accurately described a linear responses individual drugs genome...
Identifying target promoters of active enhancers is a crucial step for realizing gene regulation and deciphering phenotypes diseases. Up to now, several computational methods were developed predict enhancer interactions, but they require either many epigenomic transcriptomic experimental assays generate cell-type (CT)-specific predictions or single experiment applied large cohort CTs extract correlations between activities regulatory elements. Thus, inferring CT-specific interactions in...
Abstract Motivation Identifying target promoters of active enhancers is a crucial step for realizing gene regulation and deciphering phenotypes diseases. Up to now, several computational methods were developed predict enhancer interactions but they require either many epigenomic transcriptomic experimental assays generate cell-type-specific predictions or single experiment applied large cohort cell types extract correlations between activities regulatory elements. Thus, inferring in...
Abstract Recombination is one of the essential genetic processes for sexually reproducing organisms, which can happen more frequently in some regions, called recombination hotspots. Although several factors, such as PRDM9 binding motifs, are known to be related hotspots, their contributions hotspots have not been quantified, and other determinants yet elucidated. Here, we develop a computational method, RHSNet, based on deep learning signal processing, identify quantify hotspot purely...
Abstract Controlling cell fate has great potential for regenerative medicine, drug discovery, and basic research. Although numerous transcription factors have been discovered that are able to promote reprogramming trans-differentiation, methods based on their up-regulation tend show low efficiency. The identification of small molecules can facilitate conversion between types ameliorate this problem working through safe, rapid, reversible mechanisms. Here we present DECCODE, an unbiased...