Articles tagged with Bioinformatics
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
Researchers have developed an algorithm to identify the protozoan Trypanosoma cruzi in photographs of blood samples taken with a mobile phone camera. The low-cost method can be reproduced and adapted for other purposes that depend on images, such as analyzing feces, skin, or colposcopies.
Researchers have developed Fanflow4Insects, a functional annotation workflow that annotates gene functions in insects. The team has annotated the Japanese stick insect and silkworm, providing valuable information for entomological research and genome editing.
Researchers developed a new machine learning method called MotifBoost that can predict infections based on limited T-cell receptor data. By focusing on short sequences of amino acids in the receptors, the approach achieved more accurate results with smaller datasets, shedding light on the human immune system's recognition of germs.
Researchers developed a mathematical model to predict the efficiency of nanoparticle delivery into cells, particularly in stem cells. They found that nanoparticles become trapped in bubble-like vesicles, preventing them from reaching their targets.
The Mount Sinai Hospital has been awarded $4.2 million over five years to establish a Proteogenomic Data Analysis Center, which will help identify potential biomarkers and drug targets for cancer and new insights into cancer biology.
A UC Riverside study reports that switching from combustible cigarettes to electronic cigarettes does not restore the nasal epithelium to that of a non-smoker. The researchers found alterations in gene expression profiles associated with cigarette smokers, indicating potential harm from prolonged EC use.
Rensselaer researchers will use a five-year grant to develop novel inhibitors of the SARS-CoV-2 virus's CLpro and PLpro proteases. The team aims to create an orally bioavailable drug that can be administered at home, with the potential for improved antiviral activity when combined with other drugs like remdesivir.
A team of scientists has developed a novel computational approach to analyze DNA sequences of thousands of bacteria, revealing previously unknown gene clusters responsible for producing metabolites of interest. The study highlights the potential of these bacterial compounds in treating colon cancer and improving treatment options.
A new machine learning algorithm called 'ikarus' has found a gene signature characteristic of tumors, distinguishing between healthy and tumor cells in various types of cancer. The algorithm was trained on single-cell sequencing data sets and demonstrated an extraordinarily high success rate in distinguishing between different cell types.
Researchers developed a machine learning model to predict NAFLD development based on gut microbiome data, showing 90% of subjects who developed the disease had subtle differences in their samples. The model combines easily measurable information from blood and microbiome data with high accuracy.
Researchers developed an algorithm to classify patients into disease subtypes based on molecular changes, enabling more targeted treatments. The tool has shown potential in a study on non-alcoholic fatty liver disease, identifying lipid biomarkers for disease progression.
A new computer-aided diagnostic tool, Deep-Lung Parenchyma-Enhancing (DLPE), uses artificial intelligence to reveal signs of pulmonary fibrosis in COVID long-haulers, helping to explain respiratory symptoms and improve disease management.
Researchers at Gwangju Institute of Science and Technology have developed a new bioinformatics pipeline, CRESSP, to investigate the mechanism underlying autoimmune diseases following SARS-CoV-2 infection. The tool identified potential epitopes responsible for COVID-related autoimmune diseases and predicted cross-reactive epitopes of di...
A recent study found that boosting the pink pigeon's numbers is not sufficient to prevent its extinction in the future. The species has a high genetic load of bad mutations, which puts it at risk of collapse if conservation efforts do not continue.
Researchers developed an algorithm to quickly identify two cancer drugs that work well together, reducing testing time from three years to eight weeks. The new method uses gene expression data to prioritize potential combinations and has been confirmed in lab tests.
Researchers have developed a refined tool to identify potentially druggable gene amplifications in tumors using epigenetic data. The new methodology improves the characterization of somatic copy number alterations up to 20% with high accuracy, reaching 100% specificity and 93.3% sensitivity.
Researchers developed a new software tool, called 'meta-transcriptome detector,' that integrates genetic sequencing analysis of hosts and their microbiomes. The tool enables analysis of gene expression activity in both microbes and hosts simultaneously, allowing researchers to spot relationships between them.
A team of researchers used a CRISPR-based approach to study the evolution of lung cancer cells, tracking their history from the first activation of cancer-causing mutations. The study revealed significant diversity between subpopulations of cells within the same tumor, with certain groups becoming more fit and aggressive over time.
Researchers have identified potential biomarkers in lupus nephritis through large-scale protein analysis, which may replace invasive tests. The study's findings could lead to more accurate diagnosis and treatment of the disease.
The study found that T-cell immunity was effective against Omicron variants in approximately 90% of vaccinated Europeans. The researchers identified a specific HLA-DRB1*03:01 variant that allowed the virus to evade immune recognition, particularly affecting individuals with this genetic variation.
A team of researchers developed a prognostic model using automated brain scans and machine learning to predict survival and recovery in severe TBI patients. The model accurately predicted risk of death and unfavorable outcomes at six months after the injury, potentially improving clinical decision-making and patient care.
A recent study by Japanese researchers found that Staphylococcus argenteus, a bacterial organism causing food poisoning, was present in 13.9% of tested chicken samples. The study also revealed cross-contamination among retail foods and slaughterhouses, suggesting a potential link between the two.
Researchers developed a bioinformatics platform called REFLECT to predict optimal combination therapies based on co-occurring tumor alterations. The tool selected combinations that resulted in improved patient outcomes across pre-clinical and clinical studies, leading to increased durable responses.
Researchers found that mutation frequencies in mitochondrial DNA of developing egg cells are lower and increase less with age compared to non-reproductive cells. This suggests a protective mechanism may keep reproductive cells relatively stable, potentially related to human propensity to reproduce at later ages.
The SAVE program, a NIH initiative, provides real-time risk assessment of SARS-CoV-2 variants on immune protection. It uses a coordinated approach to identify and curate data about these variants, their impact on immunity, and their effects on vaccine protection.
A recent study identified two main subtypes of tuberculosis based on immune response to the infection. One subtype has a better prognosis and could improve treatment options, while another has a higher risk of treatment failure and death.
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.
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.
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.
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.
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 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.
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.
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 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.
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.