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New AI Tool ‘SigProfilerExtractor’ Identifies Mutational Signature Linked To Tobacco Smoking and Bladder Cancer

A new powerful machine learning tool, 'SigProfilerExtractor' has identified a link between bladder cancer and tobacco smoking. The study was led by researchers at the...

Eliminating the Confounder Bias – A Radical Approach for Better Identification of Cancer Drug Targets

Researchers from Jilin University have constructed a machine learning-based model that reduces confounders' effects to identify potential driver genes involved in cancer initiation and...

iNAP: An Integrated Network Analysis Pipeline for Microbiome Studies in Complex Ecosystems

Microbial network analysis is an acceptable approach to investigating microbiome and metagenomic datasets and finding insights into a complex ecosystem. Ye Deng et al....

Scientists Investigated Microbial Communities and Resistomes in Relation to Interconnected Humans, Soil, and Livestock

Antimicrobial resistance (AMR) may be reservoired in intensive livestock farms, posing a threat to surrounding communities. The gut microbiome of livestock, workers, and their...

Mathematical Modeling Bridges Chromatin Architecture with Potential in Genome Medicine

Scientists from the University of Michigan employed hypergraph theory, utilizing long sequence reads to map genome-wide multi-ways to identify chromatin architecture within the human...

Accelerating the Discovery of New Drugs with AI-based Screening Methods

The researchers from the University of Central Florida identified promising drug candidates using an AI-based tool, "AttentionSiteDTI," that uses natural language to model drug-target...

Meet “ProteinMPNN,” A Robust Deep Learning-based Protein Sequence Design Algorithm

Predicting protein structure has been revolutionized by machine learning over the past two years. A similar breakthrough in protein design has now been reported...

Microbiome Data Analysis using Differential Abundance Methods – A Benchmark Study

In order to perform an extensive benchmarking of the known tools for differential abundance analysis, the researchers from the University of Padova used a...

CheXzero: A Tool to Identify Pathologies from Unannotated Chest X-ray Images Using Self-supervised Learning

The new tool improves clinical AI design by overcoming the major hurdle of labeling datasets for model training. Scientists at Harvard Medical School and Stanford...

DeepFold: A Fast and Accurate Method for Ab Initio Protein Structure Prediction using Deep Learning Potentials

Scientists from the University of Michigan developed an open-source program, DeepFold, to quickly construct accurate protein structure models from deep learning-based potentials. In spite...

Vanderbilt University Researchers Suggest a New Mechanism for the Lipid Transporter

New research from Vanderbilt University suggests that a protein involved in the production of high-density lipoprotein (HDL) works differently than previously believed. High-density lipoproteins (HDL)...

Researchers at Tufts use Artificial Intelligence to Improve Tuberculosis Treatments

A challenge to tuberculosis treatment regimen design is the need to combine three or more antibiotics. The study shows how machine learning can provide...

MIT Biologists Develop a New Computational Approach to Gain Insights into Repetitive Protein Sequences

The computational analysis of proteins reveals that many repetitive sequences are shared across proteins and show similarities in species from bacteria to humans. MIT biologists...

Microsoft and Novo Nordisk Collaborate to Accelerate Drug Discovery and Development using Big Data and Artificial Intelligence

Novo Nordisk, a leading global healthcare company headquartered in Denmark, has entered into a new strategic collaboration with Microsoft Corp. to accelerate drug discovery...

Scientists Develop an Artificial Intelligence Tool that Could Reduce the Side Effects of Common Drugs

It may be possible for clinicians to use artificial intelligence to identify patients who are most prone to experiencing harmful side effects when taking...

Scientists Develop an Improved Method for Detecting Myeloma Bone Disease using Deep Learning Coupled Photon-counting CT

Scientists have developed a new CT technique using artificial intelligence (AI) to spot multiple myeloma-related bone diseases, using lower radiation doses than conventional CT,...

A New AI Model can Detect COVID-19 Cases by Analyzing Changes in Voice Data

A deep learning model based on voice data from crowd-sourced audio samples detects COVID-19 cases by analyzing subtle vocal changes. At an international congress of...

Researchers at Mount Sinai Determined the Crystal Structure of the SARS-CoV-2 Key Enzyme, Paving the Way for Novel Antivirals

Researchers at Mount Sinai have solved the high-resolution crystal structure of a critical enzyme of SARS-CoV-2, leading to the development of new antivirals. This...

Cancer Omics Data Analysis Simplified with a Graphical Interface-driven Bioinformatics Pipeline ‘iCOMIC’

Researchers from the Indian Institute of Technology, Madras, present iCOMIC, a tool for quickly analyzing genomic data. With iCOMIC, users can analyze whole genome...

Scientists Construct a Single-cell Level Cross-species Cell Landscape by Integrating Over 2.6 Million Single Cells

Life is based on individual cells. Landscape dynamics across species have not been compared despite extensive efforts to characterize cellular heterogeneity. A large number...

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HAL-X: Novel Clustering Algorithm for Rapid Single-Cell Data Analysis for Drug Discovery

HAL-X: A Novel Clustering Algorithm for Rapid Single-Cell Data Analysis for Drug Discovery

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The novel clustering algorithm HAL-x provides insights into single-cell clustering, bridging the biomedicine sciences for healthcare purposes. With its specificity and sensitivity, it allows...
Computational model reveals new disease patterns in ALS, Alzheimer’s, and Parkinson’s

Unraveling Diseases with Data – Machine Learning Helps Identify New Nonlinear Progression Patterns in...

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Researchers from the MIT-IBM Watson AI lab have developed a new machine learning-based model that recognizes ALS disease progression. The research will help design future...
gut microbiome associated with Carbapenemase-producing Enterobacteriaceae infections.

Understanding the Population Dynamics for AMR Burden due to Carbapenemase-producing Enterobacteriaceae in Gut Microbiome

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Scientists from A*STAR's Genome Institute of Singapore (GIS) discovered that carbapenemase-producing Enterobacteriaceae (CPE) could hide out among gut bacteria in asymptomatic humans. Long-term research...
Long non-coding RNAs (lncRNAs) in the cardiovascular system

Researchers Identified Deep Learning Tools as the Top Performers for Predicting Long Non-coding RNA

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New RNA transcripts have been discovered as a result of the growing amount of transcriptomic data. Bioinformatic tool developers have had difficulty separating long...
Integrating temporal single-cell gene expression modalities for trajectory inference and disease prediction

In a Benchmark Study, Scientists Investigated the Integration of Temporal Sequencing Modalities for Trajectory...

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Recent advancements in trajectory inferences have unfolded a new side of bioinformatics, i.e., single-cell analysis. The research group from the University of Northern Carolina...