Articles tagged with Bioinformatics
Researchers at UMC Utrecht developed a deep-learning algorithm that can identify brain tumor types within 20-40 minutes, allowing neurosurgeons to adjust surgical strategies on the spot. This technology has shown promising results and is already being used in clinical practice.
Researchers used AI to predict 3D shapes of over 215 million proteins, providing insights into their functions and evolution. The Protein Universe Atlas offers a valuable resource for scientists to explore protein diversity.
The African BioGenome Project's Open Institute hosts widely-attended workshops across Africa, fostering grassroots knowledge exchange and developing biodiversity genomics and bioinformatics curricula. Over 700 participants learned about cutting-edge technologies shaping the biodiversity and genomics field.
The WVU team evaluated Code Interpreter's features, finding it accessible to students but limited for scientists working with biological data. The plugin breaks down barriers for coding, but lacks internet access and parallel processing capabilities.
Researchers used AI to predict Z-DNA fragment locations that overlap with known mutations causing severe hereditary diseases. These fragments can influence traits and body processes, including hair color, height, weight, and cholesterol levels.
Amarda Shehu is leading a collaborative research project at George Mason University, using deep learning and experimentation to generate controlled properties in molecules. The project aims to address challenges in molecular biology, including resistant bacteria, with potential applications in antimicrobial compounds.
Researchers used a mathematical theory called the free energy principle to predict how real neural networks learn and organize themselves. The study successfully mimicked this process in rat embryo neurons grown in a culture dish, demonstrating the principle's guiding force behind biological neural network learning.
A team of bioinformaticians from Heinrich Heine University Düsseldorf developed a new tool called TurNuP to predict enzyme turnover numbers using AI methods. The tool outperforms previous models and can make predictions even for low-sequence similarity enzymes.
The study identifies 1,074 semi-extractable RNAs potentially involved in phase-separated membraneless organelles. These RNAs are enriched in repressed heterochromatin regions and act as hubs for RNA-RNA interactions.
The Biodiversity Knowledge Hub (BKH) is a one-stop portal providing access to FAIR biodiversity data and services. It enables researchers to navigate linked data, tools, and services across the entire biodiversity research cycle.
The USC PRECOG project aims to develop automated screening tools for clinicians using objective neural and physiological signal biomarkers. The team will advance interdisciplinary methods in neuroscience, linguistics, and machine learning to better understand mental health risk factors.
Researchers at Hokkaido University unveil unprecedented carrier protein-mediated ring-forming step in actinopyridazone biosynthesis. The dihydropyridazinone ring is formed through a novel machinery involving Apy3, Apy4, and Apy6 proteins.
Researchers found that viruses can insert genes into bacteria to help them adapt and survive in nutrient-depleted man-made environments. The study also identified novel immune systems against viruses in bacteria and detected antibiotic resistance genes in viruses on human skin and surfaces.
A pioneering device captures single proteins stochastically, detecting them digitally at high concentrations. This breakthrough could lay the foundation for personalized disease prevention and treatment.
Research identifies beneficial changes in immune system during pregnancy, which can lead to new treatment strategies for MS. Women with MS experience a 70% decrease in relapses during the last third of pregnancy, possibly due to epigenetic changes and hormone regulation.
Researchers developed a primer scheme for the human monkeypox virus that can be easily integrated into existing sequencing and bioinformatics infrastructure. This approach enables public health laboratories to rapidly adapt their genomic workflows in response to new outbreaks.
Researchers developed MOVA to evaluate the pathogenicity of missense variants based on their structural position. The new method showed superior performance in predicting pathogenicity, especially for hotspot mutations in ALS-causing genes like TARDBP and FUS.
Seg2Link refines AI predictions with efficient semi-automated corrections to accurately segment cells in 3D images from a stack of 2D images. This solution enables scientists to process large-scale image data more efficiently, accelerating research in fields such as medicine and biology.
Hanna Kokko, a renowned theoretical evolutionary biologist, has been awarded the Alexander von Humboldt Professorship for her groundbreaking research on the interplay between evolutionary and ecological factors. She will receive EUR 3.5 million to establish her research team and obtain necessary equipment and facilities.
Researchers developed six prediction models using machine learning algorithms to distinguish between atopic dermatitis lesions and non-lesions, achieving high AUC values. The models showed a positive correlation between sample quality and SCORAD scores, indicating improved treatment efficacy.
Researchers have developed an automated calling algorithm for determining B and T cell clonality from NGS data with greater sensitivity than previous models. The new model increases the assay's sensitivity in detecting clonality, allowing for more accurate diagnosis and monitoring of lymphoproliferative disorders.
Researchers developed a 'Skeletal Age' metric to assess impact of fractures on mortality, revealing a loss of one to seven years of life depending on gender, age, and bone site. The online calculator measures bone fragility to help doctors and patients understand fracture risks.
The human pangenome reference combines genetic material from 47 individuals, enabling a deeper and more accurate understanding of worldwide genomic diversity. This improves the detection of variants in the human genome, particularly structural variants that can have important health implications.
A new study reveals a shared molecular response to nanoparticles, linking immune activation and particulate matter exposure. The findings propose a solution to the 'one-chemical-one-signature' problem in chemical safety assessment.
The UC Santa Cruz Genomics Institute will run the Data Coordination Center for the Scalable and Systematic Neurobiology of Psychiatric and Neurodevelopmental Disorder Risk Genes (SSPsyGene) Consortium. The team will coordinate an initial selection of 250 relevant genes from nearly 30,000 protein coding genes in the human genome.
Researchers from Saarland University and Stanford University have gained new insights into the manifestations of aging at the molecular level. They found that the process of reading genetic information does not run as smoothly in older individuals, leading to physiological alterations in metabolism.
A WVU research team has created an OPTIMAL model to help students overcome fears of learning code and enhance critical thinking skills when using ChatGPT, a popular AI chatbot. The model facilitates chatbot-aided scientific data analysis and aims to improve coding skills and prompting abilities.
A team of researchers compared 1,800 de novo proteins from fruit flies and humans with computer-generated proteins, revealing small but significant differences in their stability and solubility. The study suggests that natural selection may play a role in the early emergence of these proteins.
Researchers at Nagoya University used PESI/MS/MS to analyze anthocyanins in crops, detecting 81 types of compounds in just 3 minutes. This technique simplifies and accelerates the analysis of plant metabolites, which contribute to crop quality and functionality.
Researchers at the University of Illinois have identified a novel class of ribosomal peptides called daptides, which exhibit hemolytic activity. This discovery opens up new avenues for therapeutic development and highlights the vast potential of undiscovered RiPP classes.
A new model of DNA flexibility has been developed, providing results of unprecedented quality and characterizing precision and efficiency at the computational level. The study presents a systematic and comprehensive analysis of DNA movement correlations and introduces a new method to capture them.
Rice University's assistant professor of computer science, Todd Treangen, has been awarded a $599,943 National Science Foundation CAREER Award to develop a comprehensive computational platform for detecting yet-unseen microbial pathogens. The project aims to characterize previously unseen pathogens that could pose a risk to humans.
Researchers at Osaka Metropolitan University discovered that whale shark rhodopsin can detect blue light, a common wavelength in the deep-sea environment. The unique adaptation allows the whale shark to thrive in low-temperature and low-light conditions, but also makes it less thermally stable.
A new computational technique analyzes bacterial genetic sequences to monitor the spread of antibiotic resistance over time. The study found that resistance genes most likely to spread are those on conjugative plasmids and targeting specific antibiotics, with many coming from a single source.
Richard McIndoe is leading a national research initiative to advance understanding of diabetes and obesity through the National Centers for Metabolic Phenotyping in Live Models of Obesity and Diabetes (MPMOD). The MPMOD initiative provides access to advanced testing services, including bariatric surgery on mice, to enable new insights ...
A study published in Nature Communications reveals that microbes living on the leaves of perennial crops like miscanthus and switchgrass play a crucial role in plant resilience. The research identifies specific microbial functions that could be targeted for future management, promoting crop growth and reducing environmental impact.
The CoDe tool enables precise edits to genetic codes, making vaccines safer and more effective. It can also modulate gene expression in small sections, aiding vaccine design and basic research.
A team of scientists has identified Myo5b as a potential genetic driver of uterine corpus endometrial cancer (UCEC), a fourth deadliest cancer in women. Elevated levels of Myo5B were found in UCEC samples, suggesting its role in transporting nutrient-absorbing transporters to the surface of cancer cells.
Researchers used UK Biobank image and genomic data to uncover insights into rare retinal dystrophies, a leading cause of blindness in working-age adults. The study identified new genetic associations with the thickness of photoreceptor cell layers, offering new avenues for research and diagnosis.
Researchers created a network of interacting proteins to understand the function of genes and link specific biological processes to diseases. They identified groups of proteins interacting with genes linked to over 1,000 human traits, providing insights into new targets for drug discovery and potential repurposing opportunities.
The new Cell Atlas updates reveal that 20% of all neurons in the mouse brain are inhibitory, with detailed information on morphological and electrophysiological properties. The atlas combines various datasets to create a coherent framework for simulating neural circuits.
Researchers at USC Keck School of Medicine have identified two new avenues for treating diverse forms of ALS by suppressing genes and inhibiting proteins. The findings suggest that targeting SYF2 gene suppression and PIKFYVE kinase inhibition may lead to broadly effective treatments for the disease.
A team of biostatisticians created a framework to evaluate the congruence and discordance of laboratory animals with specific human diseases. The tool removes bias from scientific interpretation of animal data for human conditions, revealing that some models mimic biological mechanisms well while others poorly.
Researchers identified 7 key symptoms of long COVID, including heart issues and joint pain, in a study of 52,461 patients. The findings could help healthcare providers diagnose and treat the condition more effectively.
A UTHSC team developed a unique community-focused COVID-19 data registry, MEMPHI-SYS, to guide public health policies and interventions nationwide. The registry collects demographic information, geographic locations, medical history, and risk factors, providing insights into the spread and presentation of COVID.
A study by the University of Tsukuba found that Siebold's beech populations on Okushiri Island have high genetic diversity, suggesting they may have persisted there since before the last glacial maximum. This challenges the assumption that island populations are less genetically diverse due to geographical isolation.
The IU Simon Comprehensive Cancer Center has created an endowed chair in cancer informatics with a $3 million gift from the Walther and Regenstrief foundations. This initiative aims to analyze large amounts of data to identify those at risk of developing cancer, optimize prevention and detection, and improve outcomes.
Hiroshima University researchers have generated a high-quality genome assembly of red perilla, allowing scientists to harness its abundance of potentially useful bioactive chemicals. The study enables targeted gene editing for enhanced phytochemical production, paving the way for new medical applications.
Heidelberg researchers decoded genetic regulation of sperm formation across various mammal species, including humans. The study revealed a time-related pattern of gene expression differences, highlighting the rapid evolution of spermatogenesis.
A meta-analysis of transcriptome data from aphids and locusts reveals that DNA replication, metabolic processes, and the mitotic cell cycle are enriched in response to crowded conditions. The study also identifies discrepancies with previous research findings, suggesting alternative explanations for gene expression patterns.
A new undergraduate research program at the University of Arizona aims to address local health issues in Arizona using a community-based approach. The PHIRE program recruits 60 students annually for training in health informatics and places them in research projects relevant to their communities.
Researchers successfully reconstructed a two-billion-year-old enzyme, shedding light on an ancient evolutionary mechanism that enables modern enzymes to work efficiently despite interruptions. The study reveals the ancestral enzyme is processive, removing correctly added nucleotide building blocks, and shows how bioinformatics and bioc...
Research reveals that brain function networks are affected differently by aging, gender, and blood immune factors. The study found correlations between cytokine clock, brain shrinkage, and gender, with females having a faster ticking cytokine clock.
Researchers developed an integrated approach to accelerate drug discovery by combining complex datasets from two screening platforms and next-generation metabolomics analysis. The new framework identified known compounds, confirmed mechanisms of action, and discovered novel compounds with unique biological signatures.
A Collaborative Research Centre investigates animal navigation using the Earth's magnetic field. The study focuses on vertebrates, including birds and fish, aiming to protect endangered migratory species.
Researchers identified genes associated with aggressive clear cell renal carcinoma, a subtype of kidney cancer. Anticoagulant therapies may enhance cancer treatment efficacy. Specific genes involved in blood clotting and insulin transport were found to be linked to disease progression.
MU researchers, including Jay J. Thelen and Dong Xu, are exploring genetic modification to increase seed oil production in camelina and pennycress for biofuel use in the aviation industry. The team aims to create a sustainable 'green energy' source as an alternative to petroleum-based fossil fuels.
Researchers developed STAARpipeline to analyze rare genetic variants, enabling comprehensive analysis of noncoding variants. The tool found significant associations in gene-centric and non-gene-centric analyses, advancing genetic research.
The use of Frictionless Data enhances both machine readability and human engagement with scientific outputs, turning articles into dynamic entities. Interactive figures enable readers to directly interact with data points, making the publication process more efficient and reproducible.
Researchers discovered a pattern of DNA mutations that links bladder cancer to tobacco smoking using a powerful new machine learning tool. The tool identified four mutational signatures, including one tied to tobacco smoking, which could lead to more customized treatments for patients with specific cancers.