Articles tagged with Bioinformatics
Autophagy is induced when ER-bound ribosomes are stalled, rescuing them from cellular harm. The ERC grant aims to decipher the role of Autophagy in rescuing stalled ER-bound ribosomes.
The African BioGenome Project aims to sequence the genomes of Africa's endemic plants, animals, fungi, and protists. This will build resilience in breeding, sustainable food systems, and biodiversity conservation, aligning with the post-2020 Global Biodiversity Framework and the United Nations Sustainable Development Goals.
A team of researchers found that evolution has an overwhelming preference for simple algorithms, leading to the emergence of highly symmetric structures in biology. This is because simple recipes are more efficient and easier to follow than complex ones, resulting in a higher probability of producing symmetrical outcomes.
Researchers created a comprehensive genomic regulatory map of a 24-hour-old zebrafish embryo, identifying millions of regulatory segments that control gene transcription. The study used single-cell technologies and machine learning algorithms to analyze genome data from over 23,000 nuclei.
A recent study reveals that parthenogenesis, a type of asexual reproduction, leads to a loss of efficiency in selecting beneficial mutations, reduced genetic diversity, and decreased heterozygosity in stick insects. This has significant implications for species' ability to adapt to changing environments.
University of Illinois researchers found a key gene responsible for increasing soybean protein content by approximately 2%. The discovery could lead to significant increases in protein production, addressing global food security issues. However, the gene's function is unclear and may involve the plant's circadian machinery.
Researchers developed an AI system called GestaltMatcher that uses facial characteristics to detect rare diseases with high accuracy. The system considers similarities between patients and can even suggest diagnoses for previously unknown diseases.
A recent study by KU Leuven and The Francis Crick Institute analyzed 2,658 tumor samples and found that 21% exhibited double mutations in both maternal and paternal DNA copies. This discovery sheds new light on the origin of mutations and their role in cancer development.
Researchers have developed a machine learning framework called dynamo that can predict a cell's path over time, including its fate and genetic changes. The tool uses data from individual cells to create mathematical equations describing the cell's trajectory.
A study by Michigan Medicine researchers found that people with diabetes have more macrophages in their fat tissue, particularly the anti-inflammatory CD206+ subtype. This subtype is unique in terms of gene expression and may play a role in the development of diabetes.
Researchers have identified a potential novel mechanism of action against drug-resistant tuberculosis (TB) caused by mutations in the EmbR protein, which binds to transmembrane kinase PknH. This study proposes a new approach for computer-aided drug discovery and has important implications for treating other critical diseases.
Researchers discovered a small fraction of diatom cells participate in sexual reproduction, while others block growth and reduce nutrient absorption. This phenomenon occurs in nutrient-rich conditions, representing a paradox for microalgae that usually compete for resources.
Two independent teams of researchers have found the molecular mechanism of action of praziquantel, the only approved drug to treat schistosomiasis. The drug binds to a specific type of channel in the cell membrane, causing calcium ions influx and resulting in worm paralysis and death.
Researchers from Hiroshima University analyzed 839 collections of genetic material to identify common features of oxidative stress. They found two genes, CRIP1 and CRIP3, downregulated during oxidative stress, suggesting a relationship with zinc homeostasis. The study also identified shared biological processes between the two types of...
A research team developed an AI framework that analyzes protein interactions to predict effective and low-toxicity cancer drug combinations. The framework, GraphSynergy, outperforms conventional models in identifying synergistic combinations.
Researchers have developed a new AI technique, MuSIC, which combines microscopy, biochemistry techniques and artificial intelligence to reveal approximately 70 components contained within a human kidney cell line, half of which had never been seen before.
Scientists sequenced Plasmodium falciparum genomes to understand malaria parasite populations and track drug resistance biomarkers. The study identified population-specific SNPs that can be used to determine transmission routes and monitor drug resistance.
Researchers at Duke University used new tools to monitor neurons and analyze machine learning data to see how zebra finches practice their courtship calls. They found that a neurotransmitter called noradrenaline shuts down variability in the song, making it more precise when performed under pressure.
Researchers create maps of senescence in heart and lung cells, comparing different types of senescent cells across the lifespan. The goal is to understand how senescent cells contribute to age-related diseases and develop therapies called senolytics.
Researchers used AI to predict Michaelis constants from substrate and enzyme structures, achieving accuracy comparable to experimental values. This breakthrough enables computers to estimate enzyme activity in seconds without experimentation.
Researchers developed a new protein treatment that prevents glaucoma from forming in mice and reduces pressure in the eyes. The study provides new targets for therapies and aims to develop an injectable treatment for patients.
A new research center will use genomic data and socioeconomic factors to better predict health outcomes in individuals of diverse ancestry. The center aims to develop computational tools to combine large datasets and analyze them for consistent relationships among admixed populations.
Researchers found that wild and hatchery coho salmon demonstrate different genetic markers for negative assortment, a common finding in mating. They are now trying to emulate the natural mating of coho salmon in a hatchery environment using genetic profile information.
The UTHealth-CPRIT Innovation in Cancer Prevention Research Training Program aims to increase cancer prevention scientists from underrepresented minority groups. The program provides a systematic method to teach career skills, problem-solving skills, team science, and transdisciplinary communication.
Researchers at TU Wien propose a new method to interpret and mine fungal genomes to predict essential genes for the production of valuable substances. The FunOrder method identifies co-evolved genes that are functionally necessary, distinguishing them from gap genes.
The BiCIKL project links biodiversity data types and classes across 14 European institutions, creating a Biodiversity Knowledge Hub for seamless access. This initiative streamlines Open Science and FAIR practices, empowering researchers with efficient tools to explore and utilize biodiversity data.
A novel mortality risk prediction method helps tailor treatment decisions and transplant needs for patients based on individual symptoms. The new tool uses a random survival forest algorithm to predict individual mortality risk curves, calculate mortality at any given time, and provide a 95% confidence interval.
QUT researchers developed a new mathematical model to enable faster solutions for complicated problems in agriculture, ecology and medicine. The method improves how to determine the 'best' intervention strategies, balancing benefits and side effects, and can be applied to farming practices and chemotherapy.
Researchers found that two drugs can suppress ACE2 protein production, reducing SARS-CoV-2 virus entry. Cigarette smoke extract and the drugs activate a receptor that inhibits ACE2 expression, making it harder for the virus to infect cells.
A team of researchers analyzed over 31 million iNaturalist records to find that highly active users primarily post observations of plants and insects, while large animals are underdocumented. The study provides insights into urban biodiversity and the distribution of biological data.
A new study using Neanderthal fragments suggests that generation intervals have fluctuated over the past 40,000 years, with human life history changing in response to environmental and cultural factors. The research found that Eurasian populations reproduced at a younger age than those in Europe, indicating a difference of 3-5 years in...
Researchers at the University of Pittsburgh School of Medicine have found that brain tissue inflammation is a key driver of Alzheimer's disease progression. By targeting neuroinflammation, they believe combination therapy could be more effective in reducing amyloid plaque formation and limiting tau fiber spread.
Researchers have identified a novel genetic marker, rs139185008, that distinguishes C9orf72 repeat expansion carriers from non-carriers in large population-based cohorts. This SNP is strongly associated with patients having a clinical diagnosis of FTLD and motor neuron disease ALS.
Researchers at Rice University are developing novel computational approaches to track environmental microbiome dynamics over time, across species and after perturbations. The team will use biofilm-based 'species abundance networks' on scaffolds to observe how they form their own genome-exchange networks.
Scientists have discovered how neurotransmitters and proteins interact to trigger neuronal responses in the brain, with implications for understanding mood disorders and addictions. The study reveals small changes in protein connections control cellular responses, enabling precise regulation of neurotransmitter effects.
Deep Longevity has adapted its blood aging clock to work with saliva samples, improving accuracy from 20.9 years to 4.7 years. The company's solution uses cell-type deconvolution to separate the composition of saliva samples.
A new study introduces K2Taxonomer, a software tool that analyzes high-throughput data to identify novel cell types within tumors and their microenvironments. The analysis of breast tumor-infiltrating lymphocytes revealed a transcriptional signature associated with better survival rates in cancer patients.
Researchers have discovered a huge diversity of alternative splicing combinations in the human brain, allowing for adaptation to specific requirements. New glutamate receptor variants, some with potential new functions, were identified using bioinformatic methods.
The Alvis tool helps bioinformaticians analyze DNA sequence data and reference genome databases for more accurate assembly results. It detects chimeric sequences, which can affect data accuracy, and produces efficient vector images for human interpretation.
Researchers from UNC Charlotte analyzed over 2,000 coronavirus genomes to clarify the origins of human infections. They found that bats are ancestral hosts of SARS-CoV-2, MERS-CoV, and other coronaviruses, with transmission occurring episodically.
Researchers discovered that certain anaerobic bacteria can use citrate synthase to catalyze citrate cleavage without consuming ATP, requiring very high CO2 concentrations. The findings suggest that this metabolic pathway may be a relic of early life and have potential applications in biotechnology.
Researchers at Baylor College of Medicine developed guidelines to select the best deconvolution method for RNA-seq data analysis. They evaluated 11 methods and identified their strengths and weaknesses in various scenarios, providing a benchmark for scientists to choose the optimal method for their needs.
A team of bioinformaticians at Saarland University have identified microRNAs as potential biomarkers for Parkinson's disease using artificial intelligence methods. They found that the level of these non-coding RNAs in blood samples can track the course of the disease, particularly in the third decade of life and from around age 70.
New study by Uppsala University researchers identifies ACE2 and integrin beta3 as potential key players in SARS-CoV-2 cell infection. The proteins interact with cellular processes of uptake and disposal, suggesting hijacking during infection.
A new approach to describing shapes uses a network representation called visibility graph, allowing for comparison and reassembly of complex shapes. The tool, GraVis, accurately quantifies shape parameters such as lobe length and cell area.
A study found that a single DNA base-pair change in a specific gene can influence whether a plant is a lark or night owl, affecting its flowering time and ability to withstand climate change. The research could help farmers select plants with clocks best suited to their location.
Researchers from University of Turku developed a new bioinformatics tool to predict microbial sensitivity to glyphosate. The tool classifies 80-90% of microbial species as sensitive or resistant, with 54% of human core gut bacterial species potentially affected.
The study analyzed a microarray dataset to identify differentially expressed genes in dilated cardiomyopathy, revealing 172 genes involved in various biological processes. The authors identified hub protein modules and key genes, including DLD and UQCRC2, which suggest potential therapeutic targets for the disease.
A University of Illinois study tracks the evolution of SARS-CoV-2 virus mutations, finding stabilization in key proteins that could improve COVID-19 treatments. The research suggests these stabilizations may help increase viral infectivity and shed light on vaccine development.
Klimov is developing a computational platform to design antibody-antigen interfaces based on DNA origami. The goal is to predict high-affinity peptide sequences that bind to tetanus toxin, targeting structured or unstructured antigen regions.
A new bioinformatics tool called DrBioRight has been developed to enable biomedical researchers to conduct routine analyses of large datasets without specialized expertise in bioinformatics or programming languages. The tool uses a natural-language interface to allow users to ask questions and receive intuitive analysis results.
Researchers developed a new software tool called WhatsHap polyphase to phase plant genomes in high resolution and with low error margins. The tool solves the problem using a two-phase process and is now available for polyploid organisms, including plants.
Researchers developed a mathematical model to predict crop performance and quality, accelerating the process of creating new plant varieties. The model was applied to soybeans and analyzed key traits such as plant height, seed yield, and oil content.
The Medical University of South Carolina (MUSC) rapidly adapted telehealth technologies to meet patients' needs during the pandemic. The hospital's four-pronged response ensured continuity of care for COVID-19 patients and continued outpatient care.
Mason researchers are providing biostatistics and bioinformatic analysis for integrating multi-omic data sets from a breast cancer cohort. The study will include correlations between proteomic, metabolomic, genomic, and/or clinical data from patients with triple-negative breast tumors.
A new hybrid signature based on DNA mutation and RNA expression patterns has been developed to predict the mutation status and survival of colorectal cancer (CRC) patients. The model achieved high accuracy and was found to be prognostic for CRC patients.
Two major microbial groups, Patescibacteria and DPANN, lack the ability to breathe, instead relying on fermentation to synthesize ATP. These microbes, found in Earth's subsurface, may be remnants of ancient forms of life that predate the evolution of respiration.
A web-based database, Archaeal Proteome Project (ArcPP), collects and makes available datasets to further research on archaea, a domain of microorganisms. The platform provides easily accessible data and expertise for analyzing proteomics studies, yielding significant new insights into archaeal biology.
Researchers at MDC developed Janggu, a universal programming tool converting genomics data into a format compatible with deep learning models. This allows for flexible and efficient analysis of large datasets, enabling the investigation of various biological questions.
Scientists at the University of Würzburg have identified thousands of cryptic HLA peptides in tumor immunopeptidomes using a novel bioinformatics method. These peptides may serve as effective targets for cancer immunotherapies and vaccines against virus-infected cells.