AIMC Topic: Sequence Analysis, DNA
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Single-cell specific and interpretable machine learning models for sparse scChIP-seq data imputation.
PloS one
Jul 1, 2022
MOTIVATION: Single-cell Chromatin ImmunoPrecipitation DNA-Sequencing (scChIP-seq) analysis is challenging due to data sparsity. High degree of sparsity in biological high-throughput single-cell data is generally handled with imputation methods that c...
Using deep learning to detect digitally encoded DNA trigger for Trojan malware in Bio-Cyber attacks.
Scientific reports
Jun 10, 2022
This article uses Deep Learning technologies to safeguard DNA sequencing against Bio-Cyber attacks. We consider a hybrid attack scenario where the payload is encoded into a DNA sequence to activate a Trojan malware implanted in a software tool used i...
Machine Learning Methods for Exploring Sequence Determinants of 3D Genome Organization.
Journal of molecular biology
Jun 2, 2022
In higher eukaryotic cells, chromosomes are folded inside the nucleus. Recent advances in whole-genome mapping technologies have revealed the multiscale features of 3D genome organization that are intertwined with fundamental genome functions. Howeve...
A successful hybrid deep learning model aiming at promoter identification.
BMC bioinformatics
May 31, 2022
BACKGROUND: The zone adjacent to a transcription start site (TSS), namely, the promoter, is primarily involved in the process of DNA transcription initiation and regulation. As a result, proper promoter identification is critical for further understa...
Machine learning sequence prioritization for cell type-specific enhancer design.
eLife
May 16, 2022
Recent discoveries of extreme cellular diversity in the brain warrant rapid development of technologies to access specific cell populations within heterogeneous tissue. Available approaches for engineering-targeted technologies for new neuron subtype...
A sequence-based two-layer predictor for identifying enhancers and their strength through enhanced feature extraction.
Journal of bioinformatics and computational biology
Mar 9, 2022
Enhancers are short regulatory DNA fragments that are bound with proteins called activators. They are free-bound and distant elements, which play a vital role in controlling gene expression. It is challenging to identify enhancers and their strength ...
DeLUCS: Deep learning for unsupervised clustering of DNA sequences.
PloS one
Jan 21, 2022
We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of prim...
Table2Vec-automated universal representation learning of enterprise data DNA for benchmarkable and explainable enterprise data science.
Scientific reports
Dec 14, 2021
Enterprise data typically involves multiple heterogeneous data sources and external data that respectively record business activities, transactions, customer demographics, status, behaviors, interactions and communications with the enterprise, and th...
GapPredict - A Language Model for Resolving Gaps in Draft Genome Assemblies.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 8, 2021
Short-read DNA sequencing instruments can yield over 10 bases per run, typically composed of reads 150 bases long. Despite this high throughput, de novo assembly algorithms have difficulty reconstructing contiguous genome sequences using short reads ...
BreakNet: detecting deletions using long reads and a deep learning approach.
BMC bioinformatics
Dec 2, 2021
BACKGROUND: Structural variations (SVs) occupy a prominent position in human genetic diversity, and deletions form an important type of SV that has been suggested to be associated with genetic diseases. Although various deletion calling methods based...
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