Articles tagged with Bioinformatics
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.
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.
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 high protein diet has been shown to improve birds' immune function and tolerance to infection by triggering the expression of immune-related genes. Birds fed a high protein diet were more resistant to infection and showed reduced symptoms compared to those fed a high lipid diet.
The Association for Molecular Pathology (AMP) has announced the election results for 2026-2027 leadership positions, including President-Elect Yassmine M.N. Akkari and Secretary-Treasurer Jonathan A. Nowak. The newly elected leaders will drive AMP's mission to advance molecular diagnostics.
The journal JMIR Human Factors is inviting submissions for a new theme issue focusing on human factors in health care education, management, and knowledge translation. The issue aims to explore current and emergent educational and training aspects of human factors, including digital competencies for healthcare professionals.
A new biological age 'clock' measures intrinsic capacity, sum of six key functions determining healthy aging. The IC Clock uses DNA methylation in blood to assess functional decline and links to healthier lifestyle choices.
Researchers discovered microbial communities thriving in glacier habitats on the Tibetan Plateau, interacting with intra- and extra-glacial ecosystems. Human activities and pollution pose a threat to these microorganisms, highlighting the need for conservation efforts.
A genetic analysis reveals that human parasites do not recently interbreed with those that infect cattle, contrary to previous concerns. This finding has implications for controlling schistosomiasis, a disease affecting over 200 million people globally.
The foundation recognizes five early-career scientists who apply computational methods to cancer research, with a focus on developing new protein designs and understanding chromatin modifications. Their work aims to improve treatment strategies and precision oncology for various cancers.
Dr. Cara Boutte is studying how certain bacteria grow by building their cell walls, which could lead to more effective antibiotics. Understanding this growth pattern could help scientists develop targeted and effective treatments for infections like tuberculosis.
Under carbon limitation, trees shift from roots to mycorrhiza for nutrient acquisition. Mycorrhizal colonization and extramatrical hyphal length increase, while root physiological activity declines.
CoVFit integrates molecular data with large-scale epidemiological data to predict the fitness of SARS-CoV-2 variants. The model was trained on mutations in the spike protein and population-level trends, enabling accurate predictions of variant fitness.
A study at the University of Trento has observed the brain activity of honey bees during sleep and identified similarities with human sleep patterns. The researchers used a combination of optical brain imaging, machine learning analysis, and computational neural modelling to analyze how sleep influences sensory perception in bees.
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.
John N. Weinstein, MD, PhD, chair of Bioinformatics and Computational Biology at MD Anderson Cancer Center, has been elected Fellow of the American Association for Cancer Research (AACR) Academy. He made significant contributions to advancing our knowledge of molecular profiles of cancer through multi-omic studies and data analysis.
A recent study found that germline variants can significantly impact protein behavior in cancer cells, driving tumor development and progression. Researchers identified 119 rare and common variants in key cancer genes that alter protein structure and abundance.
Combining AI with traditional mathematical modeling can improve cancer treatment outcomes by providing specificity and accuracy. The researchers emphasize the importance of ethically sharing health data to create reproducible science, protecting patient privacy while promoting scientific integrity.
Researchers found that genes near the origin of DNA replication are crucial for rapid cell growth, contradicting previous assumptions about gene distribution. The study reveals an evolutionary advantage for bacteria with optimally placed genes.
Research reveals pregnancy-induced immune shifts affecting disease susceptibility and delivery outcomes, with adaptations in T cells, B cells, and monocytes identified across stages.
Kelsey Coffman, assistant professor at UTIA, is honored for her research on beneficial viruses in parasitoid wasps and their impact on insect interactions. She has received the Insects 2024 Young Investigator Award for her significant contributions to entomology.
Researchers developed tomoseqr, a user-friendly software to estimate 3D spatial gene expression distribution. The software successfully reproduced known gene expression patterns and mapped the 3D spatial distribution of genes in zebrafish and planarians.
Researchers at ELTE have created an online database of snoRNAs in zebrafish, revealing 67 previously unknown snoRNAs and providing a comprehensive analysis of their expression during development and in adult tissues. The findings may help create better zebrafish disease models and aid understanding of complex human diseases.
Researchers at MD Anderson have made significant breakthroughs in understanding pancreatic cancer's evolutionary process and developing new treatment strategies. They also discovered that surgical resection can enhance antitumor response in patients receiving immune checkpoint therapy for advanced kidney cancer.
Scientists have uncovered the molecular structure of Mycoplasma mobile's twin motors that power its gliding ability, using cryo-electron microscopy. The complex structure reveals a new mechanism by which energy from ATP hydrolysis is converted into motility.