AIMC Topic: Genome, Human
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Deep learning-assisted genome-wide characterization of massively parallel reporter assays.
Nucleic acids research
Nov 11, 2022
Massively parallel reporter assay (MPRA) is a high-throughput method that enables the study of the regulatory activities of tens of thousands of DNA oligonucleotides in a single experiment. While MPRA experiments have grown in popularity, their small...
MAMnet: detecting and genotyping deletions and insertions based on long reads and a deep learning approach.
Briefings in bioinformatics
Sep 20, 2022
Structural variations (SVs) play important roles in human genetic diversity; deletions and insertions are two common types of SVs that have been proven to be associated with genetic diseases. Hence, accurately detecting and genotyping SVs is signific...
A deep learning framework for characterization of genotype data.
G3 (Bethesda, Md.)
Mar 4, 2022
Dimensionality reduction is a data transformation technique widely used in various fields of genomics research. The application of dimensionality reduction to genotype data is known to capture genetic similarity between individuals, and is used for v...
The reactome pathway knowledgebase 2022.
Nucleic acids research
Jan 7, 2022
The Reactome Knowledgebase (https://reactome.org), an Elixir core resource, provides manually curated molecular details across a broad range of physiological and pathological biological processes in humans, including both hereditary and acquired dise...
A Method for Localizing Non-Reference Sequences to the Human Genome.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2022
As the last decade of human genomics research begins to bear the fruit of advancements in precision medicine, it is important to ensure that genomics' improvements in human health are distributed globally and equitably. An important step to ensuring ...
Decoding the effects of synonymous variants.
Nucleic acids research
Dec 16, 2021
Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs su...
Epitome: predicting epigenetic events in novel cell types with multi-cell deep ensemble learning.
Nucleic acids research
Nov 8, 2021
The accumulation of large epigenomics data consortiums provides us with the opportunity to extrapolate existing knowledge to new cell types and conditions. We propose Epitome, a deep neural network that learns similarities of chromatin accessibility ...
Integrative machine learning framework for the identification of cell-specific enhancers from the human genome.
Briefings in bioinformatics
Nov 5, 2021
Enhancers are deoxyribonucleic acid (DNA) fragments which when bound by transcription factors enhance the transcription of related genes. Due to its sporadic distribution and similar fractions, identification of enhancers from the human genome seems ...
A sequence-based deep learning approach to predict CTCF-mediated chromatin loop.
Briefings in bioinformatics
Sep 2, 2021
Three-dimensional (3D) architecture of the chromosomes is of crucial importance for transcription regulation and DNA replication. Various high-throughput chromosome conformation capture-based methods have revealed that CTCF-mediated chromatin loops a...
Implementing FAIR data management within the German Network for Bioinformatics Infrastructure (de.NBI) exemplified by selected use cases.
Briefings in bioinformatics
Sep 2, 2021
This article describes some use case studies and self-assessments of FAIR status of de.NBI services to illustrate the challenges and requirements for the definition of the needs of adhering to the FAIR (findable, accessible, interoperable and reusabl...
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