BCB

In various applications, such as computer vision, medical imaging, and robotics, three-dimensional (3D) image registration is a significant step. It enables the alignment of various datasets into a single coordinate system, consequently providing a ...

Adolescent idiopathic scoliosis (AIS) is a complex condition characterized by abnormal spinal curvature, and surgical intervention is often required to correct the deformity. However, there is significant variability in postoperative outcomes among ...

Accurate integration of high-dimensional single-cell sequencing datasets is important for the construction of cell atlases and for the discovery of biomarkers. Because the performance of integration methods varies in different scenarios and on ...

Metabolomics-based diet assessment and diet-specific biomarker metabolites identification are becoming ubiquitous. Existing studies offer a limited understanding of the underlying biochemical dynamics due to a lack of information on the holistic ...

Graph machine learning algorithms are being commonly applied to a broad range of prediction tasks in systems biology. These algorithms present many design choices depending on the specific application and available data, making it difficult to choose ...

This paper presents a novel approach to active learning that takes into account the non-independent and identically distributed (non-i.i.d.) structure of a clinical trial setting. There exists two types of clinical trials: retrospective and ...

Three-dimensional (3D) genome states are closely related to cancer development. Nonetheless, the 3D genome information has not been clinically utilized to the best of our knowledge, due to the costly production of Hi-C data which is a manifest source ...

One of the challenges in RNA-Seq studies is finding subsets of genes that share a common mechanism of action or are associated with a regulon/pathway. Existing approaches often extract modules that reflect quantitative similarities (such as genes with ...

The identification and prediction of variation in genetic data can be explored using graph-based machine learning methods. In particular, the comprehension of phenotypic effects at the cellular level is an accelerating research area in ...

As the field of tumor phylogenomics matures, numerous methods have been developed to infer tumor phylogenies from many types of sequencing data. The tumor phylogenies being inferred have transitioned from abiding strictly to the Infinite Sites ...

Rare disease diagnosis is very challenging due to the rarity and lack of scientific knowledge. Many patients with rare diseases take years to get diagnosed and many stay misdiagnosed or are not diagnosed. Comparing with traditional diagnosis ...

Tensor Canonical Correlation Analysis (TCCA) is a commonly employed statistical method utilized to examine linear associations between two sets of tensor datasets. However, the existing TCCA models fail to adequately address the heterogeneity present ...

Complex repetitive regions (also known as segmental duplications) in eukaryotic genomes often contain essential functional and regulatory information. Despite remarkable algorithmic progress in genome assembly in the last twenty years, modern de novo ...

As health-related decision-making evolves, patients increasingly seek help from additional online resources such as "Dr. Google" and ChatGPT. Despite their potential, these tools encounter limitations, including the risk of potentially inaccurate ...

Accurately inferring the root causes of disease from sequencing data can improve the discovery of novel therapeutic targets. However, existing root causal inference algorithms require perfectly measured continuous random variables. Single cell RNA ...

Identification of semantic subheadings in biomedical article abstracts helps individuals find relevant literature at a faster pace. Prior research presented a wide range of techniques to structure abstracts and achieved high precision and recall ...

The COVID-19 pandemic forever underscored the need for bio-surveillance platforms capable of rapidly detecting emerging pathogens. Oxford Nanopore Technology (ONT) couples long-read sequencing with in-field capability, opening the door to real-time, ...

Just as a phylogeny encodes the evolutionary relationships among a group of organisms, a cophylogeny represents the coevolutionary relationships among symbiotic partners. Both are primarily reconstructed using computational analysis of biomolecular ...

3D skeleton motion recognition plays a crucial role in the field of human action recognition (HAR) due to its efficiency and reliability. This paper introduces data augmentation techniques applied to skeleton data with the aim of improving the ...

Identification of known genetic traits and disease-related variants within an individual requires a fundamental task: genotyping a set of variants from a database. However, the efficiency of this process is challenged by the growing volume of ...

The unprecedented scale of the COVID-19 pandemic created an alarming shortage of healthcare resources. To enable a more efficient resource allocation and targeted treatment, in this manuscript, we conducted a data-driven study of COVID-19 patients to ...

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated (Cas) proteins serve as a formidable defense mechanism for bacteria against foreign DNA; on the other hand, some bacteriophages (phages) and other mobile genetic ...

Traditional and state-of-the-art approaches for inferring gene regulatory networks (GRNs) weight interactions based on gene expression data. We diverge from this paradigm by introducing a novel weighting method that utilizes regulatory potential (RP) ...

This study applies machine learning (ML) feature analysis to an array of multi-functional neurocognitive symptoms specific to individuals with Parkinson's Disease (PD). We provide a framework that can assist with modernizing and objectively ...

Mammographic breast density is an early indicator of a patient's risk for breast cancer development. Although the direct cause is not fully understood, increased mammographic breast density increases the chance of developing breast cancer. Based on ...

Stroke is a significant cause of mortality and morbidity, necessitating early predictive strategies to minimize risks. Traditional methods for evaluating patients, such as Acute Physiology and Chronic Health Evaluation (APACHE II, IV) and Simplified ...

For training and testing enhancer-promoter interaction (EPI) classifiers, the question on which non-positive EPIs are selected as negative instances must be answered. Most previous methods use the dataset of the EPI classifier TargetFinder where ...

In pediatric heart transplantation, manual annotations with interob-server and intraobserver variability among cardiovascular pathology experts lead to significant disagreements about the severity of rejection. Artificial intelligence (AI)-enabled ...

Synonymous codons, which encode the same amino acid in a protein, are known to be used unequally in organisms. Prior research has been able to uncover "preferred" codons that are often found in more highly expressed genes. This has enabled different ...

Upon entering a hospital with a bacterial infection, patients are given an empirical antimicrobial therapy as a stabilizer until a proper antimicrobial agent can be determined and given. To select a proper antimicrobial agent, Minimum Inhibitory ...