Articles tagged with Sequence Analysis
The first complete marmoset genome is now available, providing a high-quality reference for studying complex diseases like Alzheimer's. The new genome reveals variation in genes linked to Alzheimer's disease, as well as immune system genes and previously un-catalogued ribosomal DNA genes.
Researchers have developed an algorithmic tool called CytoSignal that can analyze spatial transcriptomic data to infer cell-cell communication. The method can identify defective signaling interactions underlying diseases and potentially lead to new treatments by targeting specific receptor proteins.
Researchers at PolyU have pioneered a method to store digital data using engineered proteins, achieving high storage efficiency and capacity. They overcame challenges of variable amino acid sequences and degraded proteins by designing a protein template, successfully expressing and retrieving data.
A new mathematical model called LFSPRO was developed to predict the risk of Li-Fraumeni Syndrome. The model provides a more quantitative risk estimate for individuals who would benefit from testing but do not meet established criteria.
HSE researchers train a neural network, GSMFormer-PPI, to predict protein–protein interactions by integrating three types of data: sequence, structure, and surface properties. The model achieves 95.7% accuracy, outperforming popular graph-based models.
A team from Emory University developed a simple method to test the accuracy of protein language models, which are used to analyze complex biological data. By comparing how these models 'embed' natural proteins versus synthetic ones, researchers can estimate their reliability and improve their performance.
Researchers developed an AI tool called PathogenFinder2 that can detect harmful bacteria before they infect humans. The tool uses protein language models and has been shown to significantly improve the detection of bacterial threats.
A new tool, metapipeline-DNA, automates and standardizes genome sequencing analysis, reducing the complexity of large and complicated data. The open-access resource, developed by Sanford Burnham Prebys and the University of California Los Angeles, aims to improve collaboration and reproducibility across research labs.
Researchers developed a new computational approach to predict chemotherapy response in triple-negative breast cancer, outperforming current methods. The TmS biomarker accurately sorts patients into those with favorable or poor prognosis, highlighting its potential as an effective starting point for patient stratification.
The Gabriella Miller Kids First Data Resource Center has released its 37th study on extracranial germ cell tumors, a rare group of childhood cancers. The dataset comprises information from 393 children and young adults, including inherited genetic data and tumor-specific changes.
The Gabriella Miller Kids First Pediatric Research Program has released its 36th study, introducing significant new data updates to two existing studies. These advances aim to uncover the genetic foundations of childhood cancers and congenital conditions. With over 110,000 data files available, researchers can explore publicly accessib...
HTGAnalyzer is an automated tool simplifying complex transcriptomic workflows, enabling clinicians without bioinformatics expertise to perform essential analyses in precision medicine. The tool has been validated using multiple datasets and identified differentially expressed genes linked to cancer diagnosis, treatment, and prognosis.
Researchers developed a new analysis method for CoVerage that predicts SARS-CoV-2 Variants of Concern (VOCs) with a lead time of almost three months. The tool analyzes genomic data to identify antigenic changes in the virus, enabling early detection and characterization of VOCs.
Scientists have developed a new tool named scICE to tackle the stability problem in single-cell RNA sequencing data. The tool provides a way to validate clustering outcomes mathematically, ensuring higher confidence in conclusions drawn from single-cell data.
Researchers at Cold Spring Harbor Laboratory have developed a unified theory for gauge freedoms in models of biological sequences, which could revolutionize fields like plant breeding and drug development. The new approach provides efficient formulas for scientists to interpret research results with greater confidence.
A new computational tool, CellWalker2, integrates different forms of biological data to reveal relationships between cell types. The tool identifies precise cell types and assigns broader labels based on hierarchical relationships, enabling scientists to compare cell types across experiments and species.
The release of long-read sequencing datasets for two Kids First studies provides a fuller understanding of how genetics contributes to childhood cancers and congenital disorders. The datasets include improved genome assembly capabilities, facilitating variant discovery and potential targeted therapy development.
A team of researchers has comprehensively predicted the location of non-B DNA structures in great apes using newly available telomere-to-telomere genomes. The study suggests that non-B DNA is enriched in these segments and may play a role in genetic diseases and cancer, with potential new functions discovered.
A new method for DNA detection uses heterogeneous probe particles and laser light to accelerate genetic analysis. This PCR-free technique offers greater sensitivity and speed than traditional methods, making it more accessible for medical, environmental, and personal health applications.
A new genomics tool, refget Sequence Collections, streamlines genomic research by standardizing reference sequences. This enables scientists to compare data more efficiently and accelerate medical breakthroughs.
A multicenter study found targeted next-generation sequencing to significantly outperform traditional culture methods in detecting urinary tract infections, including polymicrobial cases. The method's detection time was notably shorter, with high concordance rates for both culture-positive and negative samples.
Researchers discovered a novel coronavirus in bats in Brazil with similarities to the Middle East respiratory syndrome virus. The five bats belonged to two species and showed significant genetic diversity, prompting experiments to determine whether it can infect humans.
Researchers developed a deep-learning framework, STAIG, to automatically map distinct genetic activity to tissue regions without manual alignment. The study demonstrates superior performance across various conditions, showcasing its potential for cancer research and understanding complex biological systems.
Researchers from Yale University and Altos Labs have identified age-invariant genes that stay the same across all tissues during aging. These genes are linked to essential cellular functions, challenging the common belief that gene dysregulation drives aging.
A new test called EpiAgePublic estimates biological age using only three DNA sites in the ELOVL2 gene, simplifying traditional methods while maintaining accuracy. The study found that EpiAgePublic accurately tracks aging patterns and can identify factors accelerating the aging process.
A study published in iScience reveals that bacterial species are transferred between both individuals during sexual intercourse, and these species can be traced to a partner's unique genital microbiome. This discovery may provide a new tool for identifying perpetrators of sexual assault.
Researchers at KAIST have discovered a molecular switch that can induce cancer reversal by capturing the moment of critical transition before normal cells become irreversibly cancerous. The technology uses single-cell RNA sequencing data and computer simulation analysis to identify the molecular switch.
Researchers at U of T have developed a new platform called smol-seq that uses DNA sequencing to detect metabolites. This method enables the analysis of hundreds of metabolites simultaneously, making it faster and more precise than current methods.
A new computational tool, PsiPartition, simplifies genetic data analysis for evolutionary biology, allowing researchers to efficiently study species relationships. The novel method improves both computational efficiency and accuracy of phylogenetic trees.
A new software package called TraitTrainR offers a framework for replicating the evolutionary process many times over. It can perform flexible evolutionary experiments through probabilistic simulations on a computer, allowing researchers to generate thousands-to-millions of evolutionary replicates.
Researchers have developed a method to stretch and immobilize single DNA molecules, enabling detailed analysis. By controlling the shear force applied through liquid pressure flow and bonding the molecule to a substrate, scientists can distinguish between tiny biomolecular features with higher precision.
A new DNA sequencing test called AR-ctDETECT has been found to distinguish between patients with poor and favorable prognoses in advanced prostate cancer. The test identified circulating tumor DNA in 59% of patients and showed that detectable ctDNA was associated with worse overall survival.
Researchers at UCLA Health presented several breakthroughs at the San Antonio Breast Cancer Symposium, including improved survival rates for advanced breast cancer patients who receive trastuzumab deruxtecan (T-DXd), a novel ADC. Additionally, new genomic testing and circulating tumor DNA analysis may help identify high-risk patients a...
A new framework developed by UCLA researchers suggests that genetic data from large libraries of sequenced human genomes can improve the predictive power of genetics in determining how well a patient will respond to commonly prescribed medications and the severity of any side effects. The study, which analyzed data from over 342,000 pe...
A landmark photosynthesis gene discovery has been made in a poplar tree that enhances plant growth by up to 200% and increases biomass production. The gene, named Booster, has the potential to boost crop yields without requiring more land, water or fertilizer.
Researchers from NUS and A*STAR have discovered a connection between the regulation of alternative splicing in different cell types and the predisposition to autoimmune diseases. The study used a population-scale single-cell gene expression profiling dataset to analyze splicing events specific to particular cell types, revealing ancest...
Researchers found a strong link between depression and menstrual pain in a new study published in Briefings in Bioinformatics. Depression may be a cause of dysmenorrhea, rather than a consequence, according to the findings.
A groundbreaking metagenomic sequencing test has proven effective in rapidly diagnosing almost any kind of pathogen, including viruses, bacteria, fungus or parasite. The test analyzes all nucleic acids present in a sample, replacing multiple tests with a single one and speeding up diagnosis.
Researchers at Kumamoto University have developed a cutting-edge diagnostic tool, Intelli-OVI, to rapidly identify emerging SARS-CoV-2 variants. This system combines advanced DNA detection technology with computational algorithms to offer a quicker and more cost-effective method of monitoring viral mutations.
Researchers from The University of Texas at Arlington are conducting a DNA analysis project to determine the genetic differences between the rare Dixon's whiptail and the common checkered whiptail. If the two species are found to be distinct, Dixon's whiptail may become eligible for endangered species protection.
Researchers developed an algorithm to analyze high-resolution spatial data from Seq-Scope and other technologies, called FICTURE. This enables scientists to see how and where a gene is expressed at microscopic resolution, improving our understanding of gene expression.
A recent FAU study reveals that mesophotic corals can replenish declining shallow reef populations with strong genetic connectivity between shallow and deep zones. The research suggests that deeper corals could be a key source of genetic diversity for shallow reefs, providing valuable opportunities for recovery and restoration efforts.
A new study provides further evidence that SARS-CoV-2, the virus responsible for COVID-19, likely originated from animals sold at the Huanan Seafood Market in Wuhan, China. The analysis of genetic data found that wildlife species such as raccoon dogs and civet cats were present at the market and may have carried the virus.
A new international study provides a list of wildlife species present at the Huanan Seafood Wholesale market where SARS-CoV-2 likely arose. Genetic material from raccoon dogs, civet cats, and other species was found in samples from market stalls.
A new study from European universities has developed a method to analyze wastewater data from seven major cities, identifying thousands of disease-causing bacteria, viruses, and antimicrobial resistance. This approach can detect potential health threats simultaneously, potentially preventing epidemics from escalating into outbreaks.
The study found H5N1 virus detected in 10 out of 10 cities and 22 out of 23 sites, but no correlation with hospitalizations. The team used viral probe capture to detect viruses in wastewater samples, revealing animal origins of the virus load
A new method, scAMF, reduces noise in single-cell RNA sequencing data while preserving crucial biological information. This enables more accurate cell type characterization and clustering. The framework also lays the foundation for constructing high-resolution cell atlases.
A new study reveals that a third of glioma cells, a type of brain tumor, fire electrical impulses. These hybrid cells combine features of neurons and glia, challenging the long-held notion that only neurons generate electric signals in the brain.
Researchers developed MUSCLE, a method that combines single-molecule fluorescence microscopy with next-generation sequencing to profile complex biological processes. The technique enables simultaneous observation of vast arrays of samples, uncovering general trends and dynamic signatures.
Researchers have sequenced the lungfish genome, which is 90 billion bases long and breaks all records for size. The study reveals that autonomous transposons are responsible for the genomic expansion, but surprisingly, the genome remains stable despite its enormous size.
The study analyzed over 1.8 million SARS-CoV-2 genome sequences to track virus variant spread and evolution. The introduction of free rapid antigen tests, mask regulations, and movement restrictions led to a significant decline in new variants entering Germany.
New research suggests that the plague may have contributed to the population decline of Stone Age farmers in Scandinavia and Northwestern Europe. Analysis of ancient DNA from bones and teeth found that 17% of individuals were infected with the plague, indicating its common presence during the late Stone Age.
Researchers at the University of Gothenburg developed an AI model called Candycrunch to automate the analysis of glycan structures in cancer cells. The model can identify abnormal structures and biomarkers in just a few seconds, accelerating the discovery of new treatments.
A new liquid biopsy method analyzes gene fragments in the bloodstream to detect and track cancer, enabling oncologists to tailor treatment approaches to individual patients. This non-invasive test can help monitor treatment success, detect cancer recurrence, and improve patient quality of life.
The RENEW system, launched in 2022, uses new research discoveries to pinpoint genetic variants causing rare diseases. Researchers successfully diagnosed 63 patients out of 1,066 undiagnosed cases with an average diagnosis time of 20 seconds.
A new study by a global consortium provides insight into how tumors evolve, shedding light on the intricate processes underlying cancer evolution. The findings define optimal algorithms to analyze tumor evolution, enhancing diagnostic accuracy and treatment planning.
Genome sequencing outperforms exome sequencing in diagnosing rare genetic diseases, revealing new clues and mechanisms. The method's advantages include detecting non-coding mutations and gene segments outside the exome.
Researchers created GraSSRep and rhea, tools that outperform current methods for handling repeats and structural variants in metagenomic data. These methods use self-supervised learning and graph neural networks to analyze microbiome data, offering new insights into biological processes and potential applications in antibiotic resistance.
Researchers investigate senescence phenotypes of human corneal endothelial cells upon treatment with ultraviolet (UV)-A. Cells exhibit enlarged morphology, increased β-galactosidase activity and decreased proliferation. UV-A-induced senescent cells show similar gene expression profiles to ionizing radiation (IR)-induced cells.
The new 'scLENS' tool overcomes challenges in single-cell transcriptomics by automatically differentiating signals from noise using Random Matrix Theory and Signal robustness test. This innovation significantly improves analysis accuracy and efficiency, enabling researchers to extract biological signals conveniently and automatically.