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K562 Cells

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Deep-learning-based three-dimensional label-free tracking and analysis of immunological synapses of CAR-T cells.

eLife
The immunological synapse (IS) is a cell-cell junction between a T cell and a professional antigen-presenting cell. Since the IS formation is a critical step for the initiation of an antigen-specific immune response, various live-cell imaging techniq...

DeepD2V: A Novel Deep Learning-Based Framework for Predicting Transcription Factor Binding Sites from Combined DNA Sequence.

International journal of molecular sciences
Predicting in vivo protein-DNA binding sites is a challenging but pressing task in a variety of fields like drug design and development. Most promoters contain a number of transcription factor (TF) binding sites, but only a small minority has been id...

DeepYY1: a deep learning approach to identify YY1-mediated chromatin loops.

Briefings in bioinformatics
The protein Yin Yang 1 (YY1) could form dimers that facilitate the interaction between active enhancers and promoter-proximal elements. YY1-mediated enhancer-promoter interaction is the general feature of mammalian gene control. Recently, some comput...

Deep-joint-learning analysis model of single cell transcriptome and open chromatin accessibility data.

Briefings in bioinformatics
Simultaneous profiling transcriptomic and chromatin accessibility information in the same individual cells offers an unprecedented resolution to understand cell states. However, computationally effective methods for the integration of these inherent ...

Predicting enhancer-promoter interactions by deep learning and matching heuristic.

Briefings in bioinformatics
Enhancer-promoter interactions (EPIs) play an important role in transcriptional regulation. Recently, machine learning-based methods have been widely used in the genome-scale identification of EPIs due to their promising predictive performance. In th...

A sequence-based deep learning approach to predict CTCF-mediated chromatin loop.

Briefings in bioinformatics
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...

Precipitate-Supported Thermal Proteome Profiling Coupled with Deep Learning for Comprehensive Screening of Drug Target Proteins.

ACS chemical biology
Although thermal proteome profiling (TPP) acts as a popular modification-free approach for drug target deconvolution, some key problems are still limiting screening sensitivity. In the prevailing TPP workflow, only the soluble fractions are analyzed ...

Nested epistasis enhancer networks for robust genome regulation.

Science (New York, N.Y.)
Mammalian genomes have multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, but it is unclear how these enhancers coordinate to achieve this task. We combine multiplexed CRISPRi screening with machine learning t...

AI-based Apoptosis Cell Classification Using Phase-contrast Images of K562 Cells.

Anticancer research
BACKGROUND/AIM: This study aimed to automate the classification of cells, particularly in identifying apoptosis, using artificial intelligence (AI) in conjunction with phase-contrast microscopy. The objective was to reduce reliance on manual observat...

Combining array-assisted SERS microfluidic chips and machine learning algorithms for clinical leukemia phenotyping.

Talanta
The disease progression and treatment options of leukemia between different subtypes vary considerably, emphasizing the importance of phenotyping. However, early typing of leukemia remains challenging due to the lack of highly sensitive and specific ...