Scientists Develop Deep Learning Models for RNA Degradation Prediction via Crowdsourcing,...
Scientists at the University of Stanford display the potential of crowdsourcing in accelerating and enhancing the research process. The study utilized two crowdsourcing platforms,...
Researchers Develop a Machine Learning Model to Predict Whether a COVID-19...
A study from Florida Atlantic University used machine learning to provide new evidence for understanding how molecular tests and serology tests are correlated and...
Pancreatic Cancer and Drug Resistance: Researchers Identify Key Metabolic Regulators
Drug resistance can be countered only by interrupting the adaptive measures taken by the cells to deflect the drug action. Scientists from the School...
Human Cell Atlas Mission: A Reference Map for Analyzing Human Health...
In order to better understand human health and to identify, track, and cure diseases, the International Human Cell Atlas collaboration is building detailed reference...
Cell Type-Specific Differential Gene Expression: A Guide Through The Available Methods
There is no one-size-fits-all approach to differential expression analysis, and the best method for a given dataset depends on the specific research question. Various...
Ten Hacks for Predicting Protein Properties from Sequences using Machine Learning
The success of machine learning-based approaches for the prediction of protein properties from their amino acid sequences can be attributed to the overall accessibility...
DrugRepo: A Scoring Algorithm for Drug Repurposing Incorporating Chemical and Genomic...
Scientists from the University of Helsinki, Finland, developed a drug repurposing scoring algorithm, DrugRepo, that predicted 6229 new drug-disease relationships across 545 diseases for...
Scientists Employed Phylogenetic Approach to Understand the Pattern of Mutation Occurance...
Phylogenetic approaches can be used to infer the order in which mutations arise during cancer progression by analyzing patterns of mutation occurrence in a...
Metagenomics and Metatranscriptomics: New Insights and Pipelines to Better Navigate Data...
Scientists at the Institute of Parasitology and Biomedicine and the University of Granada, Spain, collaborated to develop two pipelines that could automate and optimize...
TransFlow: a Fast and Efficient Snakemake Workflow for Whole Genome Sequencing...
TransFlow (Transmission Workflow), a convenient, quick, effective, and thorough WGS-based transmission analysis pipeline, is presented by Chinese researchers. TransFlow integrates a number of cutting-edge...
Federated Machine Learning Powers the Biggest Brain Tumor Study to Date...
Federated machine learning enables the largest brain tumor study ever conducted without sharing patient data by allowing researchers to securely analyze distributed datasets while...
MIT Researchers Used Large Language Models to Decode Clinical Health Records...
Researchers from MIT CSAIL employed a potent deep-learning model to extract crucial information from electronic health records that might help with personalized medicine.
The adoption...
UCL Researchers Unraveled the Hidden Patterns Involved in Patients with Multimorbidities
Researchers at University College London discovered multimorbidity and comorbidity illness trends using a dataset spanning 3.8 million patients in England. Patients and clinicians can...
A Multi-Omics Approach to Earth’s Microbiomes Project Demonstrates Microbial and Metabolite...
Contrasting sharply with the little knowledge of the microbial world's underlying structure is the rising awareness of its significance and variety. Despite recent developments...
Meet GenSLMs, A Genome-Level AI Model That Helps Track COVID Variants’...
Argonne National Laboratory researchers, together with partners from six different universities, NVIDIA, and Cerebras Inc., have collaborated to create GenSLMs, that learn the evolutionary...
Amazon’s Big Bet On Bioinformatics – Introduces Amazon OMICS – A...
Amazon Omics is a purpose-built service from Amazon Web Services (AWS) that enables customers to store, query, and analyze genomic and biological data at...
Scientists Develop a Machine Learning Model ‘DxFormer’ for Automated Disease Diagnosis
Fudan University researchers introduced DxFormer, a new automatic diagnostic framework in which each symptom is regarded as a token, formalizing symptom inquiry and disease...
A New Machine Learning Algorithm Classifies Sinonasal Tumors Based on DNA...
Scientists from Ludwig Maximilians University Hospital Munich, Germany have developed a new machine-learning method for classifying hard to diagnose sinonasal tumors. The DNA methylation...
Scientists Decipher the Molecular Subsets Involved in Brain Metastases of Melanoma
Researchers used a multi-OMICS technique and targeted sequencing (TargetSeq) to identify the processes that may govern the progression of brain metastases. Regardless of intracranial...
RNAlysis: a Gateway into RNA Sequencing Data Analysis for Less Computer-savvy...
Qualitative data analysis, understanding patterns, finding possible targets/candidates, and intuitively displaying the results are among the crucially difficult aspects of next-generation sequencing experiments. These...
Meet AlphaPeptDeep: a Deep Learning Framework for Predicting Peptide Properties from...
A research team led by Professor Matthias Mann from the Max Planck Institute of Biochemistry has developed AlphaPeptDeep. AlphaPeptDeep is a Python framework built...
ExpressionGAN: Generating Long Designer DNA Sequences On-Demand With Deep Learning
A new deep learning method developed by a team of researchers at Chalmers can generate regulatory DNA sequences that control gene expression in a...
Enhancing the Comprehensive Diagnosis of Neonatal Infectious Diseases Through Metagenomic Next-Generation...
Scientists from Xi’an Children’s Hospital have shown that metagenomic next-generation sequencing (mNGS) of cell-free DNA (cfDNA) and RNA may help detect trace infections from...
Scientists Develop Novel Machine Learning Models to Predict Comorbidities at an...
Researchers at AstraZeneca and Ono Pharmaceuticals sought to create a model that could predict the likelihood that individuals with Type 2 Diabetes Mellitus (T2DM)...
Scientists Created a High-Resolution Global Map of Clinically Relevant Antimicrobial Resistance...
Researchers from the University of Antwerp screened 17939 assembled metagenomic samples from 21 different biomes, varying in sequencing quality and depth, over 46 countries,...
Multi-platform Universal Single-cell RNAseq Data Processing Pipeline – UniverSC
Scientists at the Center for Integrative Medical Sciences Yokohama, Japan, designed a platform-independent application to run UniverSC, a wrapper for the 10X Genomics CellRanger program that...
Scientists Developed a Novel AI Blood Test ‘DELFI’ for Early Detection...
Johns Hopkins Kimmel Cancer Center researchers developed and used artificial intelligence blood testing technology. The new blood testing technology detected liver cancer in more...
FASSO: An AlphaFold-based Method Combines Sequence and Structure Orthology to Assign...
AlphaFold, a machine learning system developed by Google DeepMind, can predict the three-dimensional structures of proteins with unprecedented accuracy, leading to a better understanding...
Smartwatch ECG Signals Transformed into Diagnostic Tools for Heart Failure using...
A new study published by researchers at the Mayo Clinic has shown that a smartwatch ECG can accurately detect heart failure in nonclinical environments....
Functional Connectivity MultiVariate Pattern Analysis – A Novel Method for the...
In the article released in PLoS Computational Biology, researcher Alfonso Nieto-Castanon of Boston University describes a technique called fc-MVPA (functional connectivity Multivariate Pattern Analysis)....
A Bioinformatics Roadmap for Drug Prioritization from Cancer Genomics Data
Cancer is a complicated disease brought on by the interaction of various informational layers. Tumor origin, the appearance of genomic and transcriptomic variations, or...
CLIMB – A New Statistical Method for Improved Large Scale Genomic...
Researchers from Penn State University present CLIMB (Composite Likelihood eMpirical Bayes), a statistical tool that discovers patterns of condition specificity in a given genomic...
Researchers Introduce a Deep Learning Platform ‘OrganoID’ to Track Single-organoid Dynamics...
Recent research conducted by the research group of Savas Tay at the University of Chicago, Illinois, USA, introduced a deep learning platform, OrganoID to...
A Novel Deep Learning Framework Identifies Gene-Gene Interactions for a Given...
A deep learning framework has been developed by researchers under the direction of Tianyu Cui, a Ph.D. student in the Department of Computer Science...
Researchers Elucidated the Dynamic RNA Structurome and its Potential in Targeted...
With a thorough potential of the Ribonucleic Acids (RNA) in cellular processes, the molecule is deemed more than just being transitionary and has emerged...
Scientists Unveil High-Resolution Reference Genome of Nile Rat – A Promising...
A research team led by Yury V. Bukhman from the Morgridge Institute for Research has put forth a reference genome with haplotype-resolved assemblies and...
A Novel CRISPR-based Technique ‘MACHETE’ Investigates Copy Number Alterations in Cancer...
The post-doctoral researchers from Memorial Sloan Kettering Cancer Centre (MSK) developed an upfront and coherent way to study copy number alterations (CNA) deletions in...
Multidimensional Semantic Scan – A Presyndromic Surveillance Approach For Screening Potential...
Researchers from New York University, Carnegie Mellon University, and the New York City Health Department have joined forces to develop an automated machine-learning approach...
An International Collaborative Effort Assessed The Applications Of AlphaFold2
Teams of researchers across 18 institutes spread over 11 countries have worked together to assess the utility of AlphaFold2 (AF2) predictions in the analysis...
Large-scale Proteo-genomic Profiling of Virus-associated Liver Cancer Unveils Potential Subtypes and...
A large percentage of the global population is shown to have been affected by different types of cancer and increased mortality. Hepatocellular carcinoma, or...
Meet Deep-SMOLM: A Machine Learning Algorithm for Generating 5D Images of...
Deep-SMOLM is a deep-learning-based estimator created by Washington University in St. Louis researchers that blends machine learning, physical laws, and biological principles. At a...
Researchers Developed Machine Learning-Based Enzyme Engineering Approach by Integrating a Logistic...
A recent study published in ACS Synthetic Biology has presented an analogous level of adaptability to enzymes. A team of researchers from Osaka University...
Deep Learning Algorithms – the Future of Medical Imaging?
Research presented at the 2022 World Cancer Congress shows that deep learning algorithm outperformed radiologists in detecting head and neck cancer spread. The algorithm...
Researchers Develop a Computational Tool ‘CAMMiQ’ for Strain Level Microbial Detection...
A recent study led under the supervision of Cenk Sahinalp et al. and conducted jointly at the National Institute of Health, UCSD, and Indiana...
Meta AI Releases ESM Metagenomic Atlas: A Repository of Over 600 Million...
An extensive protein database that reveals the structures of millions of metagenomic proteins has been created by researchers under the direction of Alex Rives...
A New Approach ‘HI-CNV’ Elucidates the Effects of Copy Number Variation...
A team of researchers from the Broad Institute of MIT and Harvard, Brigham and Women's Hospital, and Harvard Medical School has demonstrated a computational...
Scientists Propose a Machine Learning-based Ensemble Framework ‘PreAcrs’ to Accurately and...
A team of researchers led by Prof. Jiangning Song from Monash University, Australia, has developed a novel ML ensemble predictor named PreAcrs that can identify...
Researchers Introduced a Deep Learning-based Label-Free Virtual HER2 Immunohistochemical Staining of...
Evident with the increasing cost and laborious work of diagnosis of cancer, using the gold standard Immunohistochemical (IHC) staining of tissues. Researchers from the...
Artificial Intelligence Strategies For Multimodal Fusion – A Path Towards Precision...
Cancer is a significant threat worldwide. In a study published in ACS Cancer, authors Bray et al. stated that cancer may overtake cardiovascular disease...
PRECILY – A Deep Neural Network-based Cancer Drug Response Predictor
Researchers from IIIT-Delhi and the University of Queensland have partnered to create Precily, a deep neural network-based modeling approach to predict the responsiveness of...
Must Read
Solving a Long-Standing Genomics Bottleneck: KAIST Proposes AI-Powered Strategy for Gene Function Prediction
KAIST and UCSD researchers proposed AI-driven strategies for microbial gene function discovery, addressing the long-standing bottleneck where many microbial genes remain uncharacterized despite advances...
AI-Powered Metagenomics: How MetagenBERT Predicts Disease From Raw DNA Sequences
Researchers from Sorbonne University and Dauphine University, France, introduced MetagenBERT, a Transformer-based framework for disease prediction directly from raw metagenomic DNA without relying on...
ToposBio Unveils Topos-1: An All-Atom Foundation Model for Intrinsically Disordered Proteins
Intrinsically disordered proteins (IDPs) are proteins that are central to neurodegenerative diseases and aggressive cancers like prostate cancer, have been considered ‘undruggable’ as structures...
CleaveNet Enables Scalable and Targeted Protease Substrate Design for Diagnostics and Therapeutics
Scientists from MIT and Microsoft Research present CleaveNet, an AI-based pipeline that merges predictive and generative modeling for end-to-end peptide (short protein) design. By...
Advancing Peptide Therapeutics with PeptiVerse’s Unified Prediction Framework
Researchers at the University of Pennsylvania developed PeptiVerse, a single platform that predicts drug-related properties of therapeutic peptides using either amino acid sequences or...