Articles tagged with Gene Prediction
A team of Princeton researchers has developed a machine-learning approach that analyzes the entire human genome to predict which genes may cause autism spectrum disorder. By identifying 2,500 potential autism genes, this new method provides a significant breakthrough in understanding the genetic basis of autism.
A study found that mice with a genetic mutation exhibiting periodic changes in locomotor activity and mood-like behaviors, similar to humans with bipolar disorder. Gene expression patterns in the brain identified circadian genes as key players in regulating infradian oscillations.
Researchers at RIKEN have discovered that calcium inside neurons regulates slow-wave sleep, with seven genes identified as critical for controlling sleep duration. The study's findings could lead to new treatments for sleep disorders and neurologic diseases associated with them.
Researchers found that deleting the huntingtin gene in adult mice does not lead to lethal consequences, offering hope for treatment strategies involving gene silencing. The study suggests that gene suppression or editing strategies may be safe for adults, but further research is needed to understand the long-term effects.
Researchers at the University of Tennessee have developed a computational approach to trace the evolutionary history of human genes more precisely. This method will help doctors identify disease-causing mutations and provide more effective treatment options for patients with genetic disorders.
Researchers at the University of Florida have identified genes that are disrupted by abnormal hormone signaling, leading to male genital birth defects. The study found a narrow window of development when genetic malformations can occur, and pinpointed 22 genes expressed in embryonic genitalia.
A new study using mathematical models estimates that gene replacement can spread quickly through populations, potentially eradicating diseases like malaria. However, the speed and efficiency of this biological control strategy also bring significant risks of unintended consequences.
Researchers found that a gene linked to PTSD severity predicts increased symptoms and thinner brain cortex in veterans returning from conflict. The study suggests a possible genetic blood test to identify at-risk individuals.
A gene associated with sudden cardiac death has been identified using implantable cardioverter defibrillator (ICD) monitoring. The GNAS gene polymorphism predicted ventricular tachyarrhythmias and sudden cardiac death in patients from the DISCOVERY trial and Oregon-SUDS study.
A study published in the Journal of Pediatrics identified salivary biomarkers that can accurately predict oral feeding readiness in preterm newborns. The researchers found that a combination of gene amplification techniques and advanced computational analysis tools can identify specific genes associated with oral feeding success.
Tel Aviv University researchers developed a computer algorithm that predicts which genetic genes are lethal to cells when overexpressed. The new algorithm, called Expression Dependent Gene Effects (EDGE), helps guide metabolic engineering to produce new chemicals in more efficient ways.
A recent study has found that the APOL1 gene variant is independently associated with a more aggressive course of disease, particularly in African-Americans. The variant is linked to twice the rate of CKD progression and loss of kidney function in those with chronic kidney disease.
A team of Nationwide Children's Hospital researchers identified a genetic mutation in the FOXP1 gene that contributes to congenital heart disease. The study found that a rare mutation in FOXP1 affects Nkx2.5 transcription factor expression, which is implicated in congenital heart disease.
Researchers have identified nearly all major genetic mutations that drive acute myeloid leukemia (AML), a fast-growing blood cancer. The study paves the way for developing personalized treatment plans based on a patient's genetic profile.
A team of researchers has created a map of gene 'shortcuts' between all human genes, simplifying the search for disease-causing mutations. This tool, called the human gene connectome, uses GPS-like principles to predict the distance and route between any two genes.
A recent study published in Science suggests that evolution can be predictable by understanding a species' genes and how external conditions affect proteins. By analyzing DNA sequences from 29 insect species, researchers found that certain traits evolve similarly due to environmental pressures.
Scientists have discovered rules that relate genes to a neuron's electrical properties and shape, increasing the likelihood of predicting brain structure and function without measuring every aspect. This breakthrough increases the feasibility of modeling the brain in silico and ushering in a new era of predictive biology.
Researchers question the validity of studies linking specific genes to complex behaviors like voting due to methodological errors and inconsistencies across multiple studies. The findings contradict current understanding of genetics' role in shaping human traits.
Researchers have developed a new catalogue of loss-of-function (LoF) variants to better understand the normal function of human genes. The study identifies over 1000 LoF variants, some of which are rare and potentially harmful, while others may not have a significant effect on health.
The study provides a comprehensive reference manual for analyzing population genomics and quantitative traits in fruit flies. The DGRP consists of 192 genetically identical lines with varying genetic variation, facilitating the measurement of traits and unlocking secrets of quantitative traits.
Researchers have created a genome-scale model called RiceNet to predict the functions of genes and gene networks in rice, accelerating the development of biofuel crops. The model, which encompasses nearly half of all rice genes, was developed using publicly available data sets and validated through experiments.
Researchers at Brigham and Women's Hospital developed a method to predict MDS patient survival by identifying specific gene mutations in their abnormal bone marrow. Nearly a third of patients had mutations in one or more prognostic genes, which could guide treatment decisions.
A new model predicts which cyanobacterial genes are central to capturing energy from sunlight and other critical processes. The model identifies key bottleneck genes that control the expression of essential proteins.
Researchers identified AEG-1 as a strong predictor of progression-free survival in patients with EGFR-mutant non-small cell lung cancer treated with erlotinib. Patients with low AEG-1 expression had longer progression-free survival compared to those with high expression.
A Georgia Tech team has sequenced the woodland strawberry genome, unlocking possibilities for breeding more flavorful and resilient crops. The research, published in Nature Genetics, used a hybrid gene prediction program to identify 34,809 protein-coding genes, with 55% assigned to gene families.
A study by Purdue University researchers found that specific chromosome imbalances in plants can lead to predictable physical defects. The team used polyploid and aneuploid plants to identify easily measured characteristics associated with imbalanced chromosomes, offering insights into correcting genetic defects.
Researchers developed an algorithm using Microsoft Excel to identify genes useful in breast cancer classification. The 20-gene signature performed well on a validation dataset, outperforming other models in terms of accuracy.
Researchers identify a critical lincRNA-p21 that suppresses multiple genes across the genome following p53 activation, playing a key role in mediating cellular response to DNA damage. This discovery opens up new avenues for understanding gene regulation and developing anti-cancer therapies.
The DOE JGI's new QC tool, GenePRIMP, helps check the quality of microbial genomic DNA sequences, reducing errors in gene annotations. With its ability to identify and correct anomalies, GenePRIMP facilitates comparative analysis and improves the overall accuracy of structural annotations.
Researchers found that the IGF1 gene variant responsible for small size in dogs is closely related to that found in Middle Eastern wolves, supporting an ancient origin. The study also suggests that smaller body size may have been desirable in densely populated agricultural societies where dogs lived indoors or in confined spaces.
Researchers created AraNet, a network that connects over 19,600 plant genes based on physical neighborhood and co-expression patterns. The network accurately predicted the functions of three uncharacterized genes in Arabidopsis thaliana, demonstrating its potential to revolutionize fundamental plant biology and agricultural research.
A team of Boston University researchers has developed a new method for engineering genetic circuits using combinatorial libraries and computer modeling. This approach enables the rapid construction of gene networks with predictable behaviors, accelerating synthetic biology research. The technique involves creating libraries of diverse ...
A study examining Asian young adults found consistent additive effects of ethnicity and ALDH2 genotype on drinking behaviors. Korean ethnicity and ALDH2 status were associated with significant variance in alcohol consumption, suggesting that genetic influences may play a role in predicting drinking behavior among this population.
UC San Diego researchers have found that analyzing groups of interactive genes can better predict the progression of chronic lymphocytic leukemia. They identified 30 subnetworks of gene expression patterns that separated patients with slow-growing and aggressive forms of the disease.
Researchers identified 39 histone modifications and a core set of 17 associated with active genes. These combinations, known as 'backbone sets,' were found to be present in more than a quarter of promoter regions, suggesting specific meanings for specific patterns of modification.
Researchers at Thomas Jefferson University have discovered that USP22 is crucial for controlling large-scale changes in gene expression in cancer cells. The study reveals that USP22 is necessary for the global changes in gene expression patterns that occur in these cells, making it a potential target for new anti-cancer drugs.
A new Mayo Clinic study identified several gene variations that predict people at high risk for ALS and Parkinson's disease. The researchers found a high-risk prediction factor for ALS (2,000 times greater than average) and for Parkinson's disease (nearly 400 times greater than average).
A new approach to gene prediction, CONTRAST, leverages multiple genomes to identify protein-coding genes with high accuracy. The technique directly learns useful features from genomic alignments, leading to significant improvements over existing methods.
Scientists have identified three genes associated with dopamine functioning in the brain, predicting individual differences in learning behaviors. These genes affect implicit reward learning and change choice strategies after negative feedback. The study offers insights into the genetic basis for learning differences and potential impl...
Researchers found a gene named JAK that disrupts DNA activity, leading to cancer in fruit flies and potentially affecting offspring. The study shows epigenetic information can be passed from parent to offspring, even if the mutation itself is not present.
Scientists have identified the HMGA2 gene, a common variant of which directly influences height. The study found that variations in this gene make some people taller than others, with 25% of white Europeans carrying two 'tall' versions and approximately 1cm difference in height.
A specific gene variant associated with attention deficit hyperactivity disorder (ADHD) may also predict better clinical outcomes and higher IQ in teens. The variant, called the 7-repeat version of the dopamine D4 receptor gene, is linked to thinner brain areas controlling attention but confers advantage only among youth with ADHD.
A new study from Mayo Clinic researchers reveals that the joint effects of common DNA variations in several genes within a well-defined biological pathway largely explain why some people develop Parkinson’s disease. The findings also predict with great accuracy at what age people might develop their first symptoms.
Researchers found that people with a specific variation of the PERIOD3 gene, which regulates morning and evening activity levels, experience poor attention and working memory during early morning hours when kept awake. Those with this gene variant spend more time in slow-wave sleep when allowed to sleep normally.
A study published in Cell Metabolism reveals that the MAT1 gene plays a crucial role in regulating energy production in heart cells. Researchers found that infant mice lacking MAT1 developed catastrophic heart failure, highlighting the importance of this gene in maintaining cardiac function.
Researchers have identified a critical gene in the circadian time-keeping system that enables animals to predict mealtime. The Period 2 gene plays a key role in the brain's ability to anticipate food availability, but not its effect on physiological coordination outside the central nervous system.
A team of scientists has identified 21 key genes that are targets of the Eyeless protein, which plays a crucial role in eye development. This breakthrough could lead to new insights into how eyes develop in fruit flies and humans, potentially shedding light on diseases related to vision.
Researchers developed a genetic profile of ovarian cancer that predicts survival and identifies key genes involved in chemotherapy response. The study used microarray analysis to identify a gene expression profile known as the Chemotherapy Response Profile, which confirms the importance of genes such as BAX.
Scientists have identified genetic variants in PPARG and CAPN10 genes that increase the risk of developing Type 2 diabetes, particularly in individuals with other risk factors. A large-scale study found that these variants can predict diabetes in high-risk individuals from families with T2D.
A study published in Nature analyzed 11,624 genes and found that around 9% have evolved too rapidly to be explained by chance. The researchers suggest that positive Darwinian natural selection is responsible for the increased rate of evolution, particularly in genes involved in immune function and sensory perception.
Researchers have found a surge in Rsf-1 gene copies in 13.2% of high-grade ovarian cancers, but not in low-grade or benign tumors. The amplification is associated with poorer survival rates, and the Hopkins scientists are working to develop targeted therapies.
Researchers identified 57 predictor genes that can accurately predict breast cancer patients' response to chemotherapy, offering a powerful tool for personalized treatment. These genetic markers can identify patients most likely to benefit from chemotherapy, potentially shifting focus away from standard treatments.
The new program predicts both protein sequences and untranslated regions, revealing novel insights into gene regulation. By identifying correct transcription start sites and spliced untranslated regions, scientists can better understand gene function and regulation.
A new software program, TWINSCAN, has been developed to predict genetic sequences in nematodes with high accuracy. The program predicts 60% of the genes in the C. elegans genome exactly, right up to the last amino acid, surpassing previous predictions.
Researchers identified a 76-gene signature that can predict disease relapse in patients with lymph-node negative breast cancer. The signature showed high sensitivity (93%) but lower specificity (48%) in predicting distant recurrence within five years.
Researchers from the University of Toronto developed a new method for predicting mammalian gene function by analyzing RNA expression patterns. They used a support vector machine algorithm to analyze over 40,000 known mouse mRNAs and predicted functions for thousands of genes, with high accuracy.
A new gene-based screen developed by Stanford researchers can accurately predict a person's response to treatment and identify patients who may benefit from novel therapies. The screen uses a technique called RT-PCR to analyze genes associated with cancer survival, offering a more accessible alternative to existing microarray technology.
Researchers have identified a set of six genes that correlate with survival in diffuse large B-cell lymphoma, including LMO2, BCL6, and CCND2. The findings suggest that molecular profiling may help refine prognoses for this difficult-to-treat blood cancer.
Researchers identified three strongly predictive genes - OPAL1, GNB2L1, and IL-10 receptor alpha - that were associated with better outcomes in pediatric ALL patients. These genes may help improve risk classification and outcome prediction for acute leukemia in children.
Researchers found that the Y chromosome contains about 78 genes and has a unique gene repair technique that allows it to preserve critical genes without sexual recombination. This discovery challenges the widely held notion of the Y's 'rotting' nature over the next 5 million years.