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...
Accurate Sepsis Diagnosis using Integrated Host-Microbe Plasma Metagenomics Profiling
Sepsis is a life-threatening condition damaging multiple organs at a time due to the host’s aberrant immune responses against infections. The current study supported...
Synergistic Protein Modeling Using AlphaFold and Density Maps Improves Structure Prediction...
A team of researchers led by Thomas Terwilliger from the New Mexico Consortium developed a procedure where the AlphaFold structure prediction models can be...
Researchers Find Clues to Protecting Crops from Blast Disease by Gaining...
Owing to the rise of global food insecurity, several initiatives have been made to understand the disease-causing plant pathogens and crop failure. Researchers from...
Data Dimensionality Reduction Promotes Stage-specific Malaria Detection Based on Neural Networks
Owing to the increase in malaria infections and morbidities associated with it, an upgradation of diagnostics gold standard procedures can help elevate the disease...
A Novel Machine Learning Method for Classifying Macrophages Could Facilitate the...
Researchers from Trinity College Dublin have introduced a machine-learning model that classifies human macrophages based on cellular autofluorescence imaging of NAD(P)H. They have also...
Genomic Insights into the Physiology of an Iconic Unculturable Rumen Bacterium...
The iconic bacterial genus from sheep rumen ‘Quinella’ has been the center of bacterial taxonomy for various reasons. The research group from Massey University,...
Artificial Intelligence Accurately Predicts Patient’s Race from Medical Images – Can...
According to the study by Prof. Judy Gichoya of Emory University, the standard deep learning models effectively predicted the patient's race using only diagnostic...
Novel EEG Phenotyping to Identify Neurological Disease from Sleep Brainwaves
Investigators from Brigham and Women’s Hospital developed a novel approach to identify time-frequency peaks from sleep brain waves revealing heterogeneity between both healthy and...
Machine Learning Model ‘CODE-AE’ Predicts Personalized Cancer Drug Response Using Cell...
A team of computer scientists from the City University of New York has created a novel framework named the context-aware deconfounding autoencoder, which is...
SQUID: A New Generative Model for Shape-Conditioned Generation of 3D Molecules for Structure-Based...
Researchers from MIT University, Cambridge, have introduced a novel generative model, 'SQUID', to facilitate the shape-conditioned generation of chemically diverse molecules for drug design...
Single-cell RNA Sequencing and GWAS Data Integration Discover New Disease Cell...
A brand-new framework called sc-linker has been proposed by researchers from the Broad Institute of MIT and Harvard that connects human illness and phenotypes...
Attention-based Multi-view Graph Collaborative Learning Model ‘stMVC’ to Decipher Tumor Heterogeneity...
Recent advancements in SRT (Spatial Resolved Transcriptomics) technology has allowed in-depth research to measure gene activity in tissue samples and map the activity based...
Demystifying Large Protein Complex Structures Using AlphaFold and Monte Carlo Tree...
Researchers from Stockholm University, Sweden, have developed a novel bioinformatics pipeline to predict the structure of large protein molecules, such as the nuclear pore...
DrugRep: An Automated and Parameter-Free Virtual Screening Tool for Drug Repurposing
Drug repurposing has been strategically used to modulate the usage of pre-existing drugs. The virtual screening tool DrugRep facilitates computational screening using both receptor...
Insurance Claim Data and Machine Learning Aids in the Early Detection...
Researchers from Pennsylvania State University have put forth a novel machine-learning approach to help predict Autism Spectrum Disorder in children at a very young...
A Systematic Proteome-scale Contactome Map Reveals How SARS-CoV-2 Communicates with Human...
Witnessing the most wrecking pandemic in a decade, COVID-19 visibly tested the potential of healthcare advancements. A collaborative team of researchers addressed earlier loopholes...
KAGE – A Fast Alignment-free Graph-based Genotyper for SNPs and Short...
Researchers from the University of Oslo have developed a novel genotyper named KAGE for detecting SNPs, short insertions, and deletions. KAGE uses an alignment-free...
Predicting Genome-Wide Chromatin Loop using Deep Learning Model ‘DLoopCaller’
Throughout the years, dissecting gene regulation has been a major challenge for researchers. Using high-throughput sequencing, understanding chromatin landscapes and conformations has set a...
Must Read
Teaching Genomics Made Easy: Meet eduomics, the Automated Omics Simulation Pipeline
When researchers at the Department of Biology and Biotechnology, the University of Pavia, set out to rethink bioinformatics teaching. They started from a simple...
Unlocking Cellular Mysteries with CellReasoner: A New AI Tool for Biologists
In the rapidly evolving field of single-cell biology, accurately identifying cell types from complex datasets remains a cornerstone of research. A team of scientists...
Minimal Data, Maximal Impact: The Future of Peptide Design with MDMI
Peptides, which are short chains of amino acids, have become increasingly important in the world of medicine and biotechnology. Their unique properties make them...
Can Machine Learning Finally Crack the Protein Expression Code?
A team of researchers from the University of Edinburgh and collaborators from institutions like Stanford and UC San Francisco have tackled a central question...
AlphaGenome: DeepMind’s New AI Model for Unlocking Genome Function
Imagine holding a book written in a language where only 2% of the pages contain clear instructions, while the remaining 98% seem like indecipherable...