Contrastive Mapping Learning for Spatial Reconstruction of Single-Cell RNA Sequencing Data

Information Science, Computer Science, Artificial Intelligence, Medicine, Life Sciences, Bioengineering,
Single-cell RNA sequencing   Spatial transcriptomics   Contrastive learning   Cell correspondence   Gene expression  

Single-cell RNA sequencing (scRNA-seq) technology enables high-throughput transcriptomic profiling at single-cell resolution, significantly advancing research in cell biology. However, a notable limitation of scRNA-seq is that it requires tissue dissociation, resulting in the loss of the original spatial location information of cells within tissues...

Efficient Storage and Regression Computation for Population-Scale Genome Sequencing Studies

Information Science, Computer Science, Life Sciences, Bioengineering, Genetics,
genome sequencing   data compression   regression analysis   computational efficiency   rare variants  

With the increasing availability of large-scale population biobanks, the potential of Whole Genome Sequencing (WGS) data in human health and disease research has been significantly enhanced. However, the massive computational and storage demands of WGS data pose significant challenges to research institutions, especially those with limited funding ...

Predicting circRNA–Disease Associations with Shared Units and Multi-Channel Attention Mechanisms

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Bioengineering,
circRNA   disease association   multi-view learning   attention mechanism   contrastive learning   computational model   bioinformatics  

Background Introduction In recent years, circular RNAs (circRNAs), as a novel class of non-coding RNA molecules, have played a significant role in the occurrence, development, and treatment of diseases. Due to their unique circular structure, circRNAs are resistant to degradation by nucleases, making them potential biomarkers and therapeutic target...

ACImpute: A Constraint-Enhancing Smooth-Based Approach for Imputing Single-Cell RNA Sequencing Data

Information Science, Computer Science, Life Sciences, Bioengineering,
Single-cell RNA sequencing   Data imputation   Constraint-enhancing smooth   Cluster analysis   Trajectory inference  

Single-cell RNA sequencing (scRNA-seq) technology has been widely applied in biological and medical research in recent years. It can reveal the transcriptomic information of individual cells, helping scientists better understand cellular heterogeneity and complexity. However, a common issue in scRNA-seq data is “dropout events,” which result in man...

SP-DTI: Subpocket-Informed Transformer for Drug–Target Interaction Prediction

Chemistry, Medicinal Chemistry, Information Science, Computer Science, Artificial Intelligence, Life Sciences, Biochemistry, Bioengineering,
Drug-Target Interaction   Deep Learning   Subpocket Analysis   Transformer Model   Drug Discovery  

Academic Background Drug-Target Interaction (DTI) prediction is a critical step in drug discovery, significantly reducing the cost and time of experimental screening. However, despite the advancements in deep learning that have improved the accuracy of DTI prediction, existing methods still face two major challenges: lack of generalizability and ne...

A General Debiasing Framework with Counterfactual Reasoning for Multimodal Public Speaking Anxiety Detection

Information Science, Computer Science, Artificial Intelligence,
public speaking anxiety detection   multimodal debiasing   spurious correlation   counterfactual reasoning   dataset  

Academic Background and Problem Introduction In the field of education today, Public Speaking Anxiety (PSA) is a widespread phenomenon, especially among non-native language learners. This anxiety not only affects learners’ ability to express themselves but may also hinder their personal development. To help learners overcome this issue, researchers...