Articles tagged with Bioinformatics
Researchers developed RNACOREX, a new open-source software tool that identifies gene regulation networks in cancer. The tool analyzes thousands of molecules simultaneously to detect key interactions, providing an interpretable molecular map that improves understanding of tumors.
Researchers analyzed DNA captured on air filters since the 1960s to track changes in ecosystem biodiversity. The study found a clear decline in biodiversity from the 1970s to the early 2000s, linked to human activities such as forest management.
Researchers have launched a new multimodal medical dataset, Observer, capturing anonymized, real-time interactions between patients and clinicians. The dataset links video, audio, transcripts, and electronic health records to study subtleties like body language and environmental factors affecting care.
Researchers have identified 32 causal genes that increase the likelihood of developing long COVID, including 13 new genes not previously associated with the disease. The study's findings could lead to more precise diagnoses and treatment options for the condition, which affects an estimated 400 million people worldwide.
A study analyzed large-scale human ChIP-seq data to identify unmeasured transcription factor-tissue/cell type pairs, revealing significant gaps in current knowledge. These findings indicate that essential regulatory mechanisms may have been overlooked, emphasizing the need for strategic prioritization of measurement targets.
A multidisciplinary team developed a computational pipeline called iSPy to quantify ploidy across tissues from microscopy images. This allows scientists to visualize and study polyploid cells directly in intact, living tissue, revealing spatial patterns of DNA content.
Machine learning (ML) streamlines nanomedicine development by predicting nanoparticle parameters and optimizing drug release profiles. ML models can personalize therapeutic regimens for individual patients, addressing longstanding challenges in cancer therapy.
A recent study found that potassium sorbate, a widely used food preservative, can induce acute kidney injury by disrupting cell-to-cell communication. The research identified amyloid precursor protein as a key regulator of this process.
An international team led by Lehigh University researcher Hannah Dailey is building predictive models to understand and eventually prevent bone healing complications. The team aims to incorporate biological differences into the model, using a library of imaging data from Switzerland's AO Research Institute Davos.
A new computational tool called DeepTarget predicts direct and indirect targets of cancer drugs, revealing that small molecules can have different targets and effects depending on the disease and cell type. The study demonstrates the tool's superior performance in real-world scenarios, highlighting its potential to accelerate drug deve...
Researchers identified a genetic marker, PAV284, associated with increased salt tolerance in sorghum seedlings. The SbTEF1 gene plays a role in regulating root growth under saline conditions.
Researchers developed a 'humanized' model of aortic valve calcification, enabling testing of potential treatments. The breakthrough could lead to new therapies to stop or reverse calcium buildup, improving outcomes for people with heart disease.
A new study published in iMetaMed uses single-cell Raman spectroscopy to track biochemical changes in mouse oocytes as they age, revealing a decline in metabolic maturity. The research suggests that mitochondrial dysfunction plays a key role in the age-related decline of egg cell quality.
Malignant mesothelioma of the tunica vaginalis testis has a global incidence of 0.54-0.95 per 10 million person-years, with asbestos exposure being a major risk factor. The expert consensus aims to shift clinical practice from empirical treatment to evidence-based, personalized care for patients with this rare disease.
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.
A new resource identifies genetic variants associated with elevated 'bad' cholesterol, a major contributor to heart disease. Clinicians can now predict patient risk for heart attacks and strokes, allowing for prevention and early treatment.
SeqHub enables rapid interpretation of proteins and genomes using AI-driven function prediction, context, and structure. The platform aims to accelerate discovery in biology by making sequences more searchable, interpretable, and engineerable.
Researchers at the University of Missouri are exploring the use of extracellular vesicles to target lung cancer. By manipulating these tiny messenger particles, scientists can deliver specific instructions to kill cancer cells while sparing healthy ones.
MARTi enables rapid taxonomic classification and abundance analysis of microorganisms in various settings, including agriculture, environmental monitoring, and clinical environments. The tool provides immediate analysis results, allowing for quick identification and targeted treatments of pathogen infections.
Researchers introduce theoretical foundations of HMMs, including evaluation, decoding, and learning algorithms, for applications in bioinformatics such as transmembrane protein prediction and gene finding. HMMs are expected to remain central to advancing genome annotation and functional genomics.
Researchers at HUN-REN Szegedi Biológiai Kutatóközpont have developed an AI-powered platform for automated 3D cell culture analysis, enabling high-precision screening of cellular models. The technology removes the limitation of throughput in personalized medicine, allowing for fast and accurate analysis of clinical samples.
University of Missouri researchers are helping farmers prevent disease outbreaks by teaching biosecurity practices, such as hand sanitizing and wearing farm-dedicated shoes. They also provide guidance on safe composting methods to dispose of dead livestock, reducing the risk of disease spread.
AI accelerates pathogen evolution prediction and enables new target discovery, facilitating efficient compound design and optimization. This technology compresses the development cycle by focusing on key applications like phenotype-driven target identification and validation.
A new large language model, LassoESM, has been developed to predict lasso peptide properties, enabling the acceleration of rational design for biomedical applications. The model was trained on thousands of lasso peptide sequences and demonstrated accurate prediction of various properties.
A new project aims to enhance workforce readiness in molecular bioscience by creating open-access resources and modules tailored to student needs. The Molecular Data Education Hub will host instructional materials and case studies for instructors to implement into their courses.
Researchers from Ateneo de Manila University have identified key proteins produced by Helicobacter pylori that can trigger a strong immune response. By analyzing these proteins using immunoinformatics, the team has pinpointed potential vaccine targets to prevent stomach ulcers and cancer.
The bregr R package streamlines the process of analyzing large-scale biomedical data by automating model fitting, extracting tidy results, and providing publication-quality visualizations. This results in enhanced efficiency and scalability for researchers, while maintaining reproducibility and accuracy.
The E2E R package offers a comprehensive framework for ensemble learning, combining multiple base models to enhance prediction accuracy and robustness. It achieved excellent performance on imbalanced datasets, outperforming mature algorithms in Python.
The University of Texas at Arlington is hosting its fifth annual Texas Health Informatics Alliance Conference, which will delve into the ethical and effective applications of artificial intelligence in healthcare. Keynote speakers and panel discussions will explore topics such as AI security, cybersecurity, and legislative outcomes.
Researchers found that children with stable gut microbiomes tend to have better growth outcomes. The study created the first-ever pediatric undernutrition microbial genome catalog, which can predict and prevent malnutrition. This discovery opens the door to new diagnostics and therapeutics for addressing global child stunting issues.
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...
Researchers found that combining arbuscular mycorrhizal fungi with biochar can reshape soil microbiomes, reduce cadmium uptake, and improve plant growth. The treatment resulted in up to 320% greater shoot biomass compared to untreated controls.
A big data study using multi-omics data from over 1,300 people with HIV has identified key molecular players causing non-AIDS-related comorbidities. The research reveals a range of previously hidden molecular patterns and players associated with various comorbidities.
Researchers developed a machine learning model that accounts for biological variability to identify optimal formulations for serum-free culture media. The model achieved approximately 1.6-fold higher cell density compared to commercially available products.
Researchers develop AI-based model for structural analysis of antibodies, offering precision in less time. The S2ALM model integrates sequence and structure, predicting missing information with high accuracy.
Researchers used gene expression data to identify genes related to stress responses in wild varieties, which could be beneficial for developing hardier crops. Domesticated species showed genes related to hormone regulation and chemical detoxification.
Researchers have published near-complete reference genomes of the central bearded dragon, a species where sex is influenced by both genetics and environmental factors. The assembled genomes revealed key genes, including Amh and Amhr2, that play a crucial role in male sexual differentiation.
Researchers at the University of Graz and the University of California, San Diego have developed a novel method to determine omega positions of lipids in complex biological samples. This breakthrough enables the study of biological mechanisms in unprecedented detail, particularly for inflammation-related diseases.
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.
The CPADS web tool integrates data from GEO, TCGA, and GDSC databases to analyze gene expression changes, correlations between genes or drugs, and pathway enrichment in cancer samples. L1CAM was identified as a potential drug resistance target in non-small cell lung cancer through CPADS analysis.
The THER web tool analyzes hypoxia-associated transcriptomic data without programming skills, presenting results via volcano plots, heatmaps, and tables. Experimental validation confirms THER's reliability, revealing broad impacts of hypoxia on drug efficacy across tumor types.
Study identifies genes functional in fetal brain stem cells linked to various brain diseases, including autism, depression, and Alzheimer's. Understanding these mechanisms can lead to targeted therapies and personalized treatments.
A recent study using deep genome skimming reveals the complex evolutionary history of Adenophora and its allies within the Campanulaceae family. The research shows that hybridization played a crucial role in shaping their phylogenetic relationships, leading to redefinition of genera and subspecies.
CORNETO enables researchers to extract molecular networks by combining experimental data with prior biological knowledge, helping to better understand cell health and disease mechanisms. The tool identifies shared pathways and patient-specific differences, a step toward personalised treatment strategies.
A new study developed an innovative dynamic biomarker system to identify 'tipping points' in thyroid cancer progression and subtypes. The system, TCPSLevel, captures early-warning molecular signals and outperforms traditional staging in identifying high-risk individuals.
A comprehensive dataset of proteins participating in liquid-liquid phase separation (LLPS) has been created to overcome limitations of existing algorithms. The dataset classifies proteins into drivers and clients, and provides a standard set for training AI systems, enabling more precise computational tools.
A new study reveals B cell-derived ELL2 as a promising biomarker for diagnosing and predicting the prognosis of sepsis. The research identified three subtypes with significantly different prognoses, which were consistently reproduced across all cohorts.
Researchers developed IOBR to analyze interactions between tumors and immune systems, offering precision medicine and new therapeutic targets. The tool's capabilities include multi-omics data integration and visualization, enabling a deeper understanding of the tumor microenvironment.
The new GseaVis package offers highly customizable visualizations, including enrichment plots, ranked gene heatmaps, and circular layouts, addressing the limitations of existing tools. It integrates seamlessly with established R libraries and workflows, making it accessible to researchers at various skill levels.
Researchers discovered that amino acids constantly communicate through a dynamic network within cells, modulating the cellular response to different stimuli. This knowledge may lead to more accurate and targeted treatments for various diseases, avoiding unwanted side effects.
Researchers developed Localizatome to study oxidative stress-related changes in protein localization. The database provides comprehensive information on subcellular protein localization and dynamic localization changes under stress.
The BA.2.86 Omicron strain was found to have emerged with a high number of genetic mutations in its spike protein, but failed to become a dominant strain. Its sporadic global detection has raised questions about the possibility of laboratory involvement in its emergence.
Researchers identified four clinically and biologically distinct subtypes of autism, each with distinct developmental, medical, behavioral, and psychiatric traits. The study linked subtypes to genetic profiles and developmental trajectories, offering new insights into the biology underlying autism.
A novel online analysis platform, PlastidHub, has been developed to facilitate plastid phylogenomic research. The platform offers improved annotation flexibility, quantitative assessment of annotation completeness, and diverse extraction modes for canonical and specialized sequences.
Gene coexpression analysis reveals optimal markers of cell types and states, providing opportunities for developing novel biomarkers and targeted treatment strategies for glioma patients. Dr. Oldham's work tackles the reproducibility crisis in science, emphasizing data metadata standardization.
A new bioinformatic tool called Cell Marker Accordion has been developed to help researchers understand single-cell analysis results. The tool reveals the presence of altered cells that may be linked to diseases such as blood cancers or solid tumours, and can identify unique genes involved in these alterations.
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 Lund University have discovered a new signalling pathway that protects against hypertension by activating a compensatory mechanism in blood vessel cells. The study found that the mice were protected against hypertension by activating this pathway, which suggests potential for future complementary blood pressure medicines.
Researchers developed Variant-aware Cas-OFFinder, a web-based tool that improves CRISPR accuracy by identifying off-target effects across genetic variations. The tool offers a significant step forward in personalized genome editing by incorporating genetic diversity directly into off-target predictions.
A new computational biology pipeline has identified 13,312 highly conserved 'universal' groups of grass genes, present across all studied grasses and responsible for vital functions. The study used a Hidden Markov Model, which outperformed a simpler approach, to distinguish between lineage-specific and non-specific genes.