Bioinformatics Research & News

Bioinformatics | COVID-19 | Health | Machine Learning | News
Multidimensional Semantic Scan – A Presyndromic Surveillance Approach For Screening Potential Public Health Threats
ByShwetha S November 11, 2022November 11, 2022
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 that detects new, upcoming health threats from local health department complaints and disease cluster data. Diseases emerge from a variety of situations that, in turn, pose a huge threat to public…
Read More Multidimensional Semantic Scan – A Presyndromic Surveillance Approach For Screening Potential Public Health Threats
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Trending
An International Collaborative Effort Assessed The Applications Of AlphaFold2
ByShwetha S November 10, 2022November 10, 2022
Teams of researchers across 18 institutes spread over 11 countries have worked together to assess the utility of AlphaFold2 (AF2) predictions in the analysis of distinctive structural elements, the impact of missense variants, the prediction of function and ligand binding sites, the modeling of interactions, and the modeling of experimental structural data. A significant biological…
Read More An International Collaborative Effort Assessed The Applications Of AlphaFold2
Big Data | Bioinformatics | Cancer Research | Drug Discovery | News | Paper Summary | Precision Medicine | RNA-Seq | Sequencing | Trending | Virus
Large-scale Proteo-genomic Profiling of Virus-associated Liver Cancer Unveils Potential Subtypes and Therapeutic Targets
ByMahi Sharma November 9, 2022October 22, 2026
A large percentage of the global population is shown to have been affected by different types of cancer and increased mortality. Hepatocellular carcinoma, or primary liver cancer is one the life-threatening disease and the fastest-growing cancer type in the United States. A recent study conducted by Hidewaki Nakagawa et al. leveraged the proteomic profiling of…
Read More Large-scale Proteo-genomic Profiling of Virus-associated Liver Cancer Unveils Potential Subtypes and Therapeutic Targets
Algorithm | Bioinformatics | Deep Learning | Machine Learning | News | Paper Summary | Structural Biology | Trending
Meet Deep-SMOLM: A Machine Learning Algorithm for Generating 5D Images of Proteins
ByShwetha S November 8, 2022November 7, 2022
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 rate ten times quicker than iterative estimators, Deep-SMOLM correctly and precisely reconstructs 5D information of simulated biological fibers and experimental amyloid fibrils from images, including highly overlapping single molecule structures. A…
Read More Meet Deep-SMOLM: A Machine Learning Algorithm for Generating 5D Images of Proteins
Bioinformatics | Biomedical Engineering | Deep Learning | News | Paper Summary | Trending
Researchers Developed Machine Learning-Based Enzyme Engineering Approach by Integrating a Logistic Regression Model
ByMahi Sharma November 7, 2022November 7, 2022
A recent study published in ACS Synthetic Biology has presented an analogous level of adaptability to enzymes. A team of researchers from Osaka University has illustrated the hypothesis to identify the amino acid residues actively involved in cofactor specificity by integrating a logistic regression model with an amino acid sequence dataset. The machine learning approach…
Read More Researchers Developed Machine Learning-Based Enzyme Engineering Approach by Integrating a Logistic Regression Model
AI | Bioinformatics | Cancer Research | Deep Learning | Health | News | Trending
Deep Learning Algorithms – the Future of Medical Imaging?
ByDr. Tamanna Anwar November 6, 2022November 6, 2022
Research presented at the 2022 World Cancer Congress shows that deep learning algorithm outperformed radiologists in detecting head and neck cancer spread. The algorithm was able to detect small areas of cancer spread that were not detected by the radiologists. This is a potentially important finding, as early detection of cancer spread can lead to…
Read More Deep Learning Algorithms – the Future of Medical Imaging?
Bioinformatics | Computational Models | Genomics | Metagenomics | News | NGS | Paper Summary | Sequencing | Tools | Trending
Researchers Develop a Computational Tool ‘CAMMiQ’ for Strain Level Microbial Detection and Quantification Using High Throughput Sequencing Data
ByMahi Sharma November 5, 2022November 5, 2022
A recent study led under the supervision of Cenk Sahinalp et al. and conducted jointly at the National Institute of Health, UCSD, and Indiana University introduced an optimized framework for strain-level microbial identification. The team has provided a comparative approach with reference to other taxonomic classifiers and embedded results with higher sensitivity and specificity. Introduction…
Read More Researchers Develop a Computational Tool ‘CAMMiQ’ for Strain Level Microbial Detection and Quantification Using High Throughput Sequencing Data
AI | Bioinformatics | Metagenomics | News | Paper Summary | Structural Biology | Trending
Meta AI Releases ESM Metagenomic Atlas: A Repository of Over 600 Million Predicted Protein Structures
ByShwetha S November 4, 2022November 4, 2022
An extensive protein database that reveals the structures of millions of metagenomic proteins has been created by researchers under the direction of Alex Rives from Meta (formerly known as Facebook). With DeepMind’s AlphaFold demystifying 220 million protein structures from DNA databases in early 2022, this groundbreaking study has surpassed these findings by unraveling 617 million…
Read More Meta AI Releases ESM Metagenomic Atlas: A Repository of Over 600 Million Predicted Protein Structures
Bioinformatics | Genomics | GWAS | Health | News | Paper Summary
A New Approach ‘HI-CNV’ Elucidates the Effects of Copy Number Variation on Human Genome and Health
ByMahi Sharma November 3, 2022November 4, 2022
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 technique called Hi-CNV to identify millions of copy number variants harboring in the human genome and link them to health-related traits such as height, lipid levels, and bone density by imposing…
Read More A New Approach ‘HI-CNV’ Elucidates the Effects of Copy Number Variation on Human Genome and Health
Bioinformatics | Biomedical Engineering | Computational Models | Machine Learning | News | Paper Summary
Scientists Propose a Machine Learning-based Ensemble Framework ‘PreAcrs’ to Accurately and Efficiently Identify Anti-CRISPR Proteins From Amino Acid Sequence
ByShwetha S November 2, 2022November 2, 2022
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 anti-CRISPR proteins from a given polypeptide sequence with good accuracy and robustness. Clustered regularly interspaced short palindromic repeats (CRISPR) is a family of DNA sequences, CRISPR-associated protein (Cas) is a family…
Read More Scientists Propose a Machine Learning-based Ensemble Framework ‘PreAcrs’ to Accurately and Efficiently Identify Anti-CRISPR Proteins From Amino Acid Sequence
AI | Bioinformatics | Cancer Research | Deep Learning | Health | News | Paper Summary | Trending
Researchers Introduced a Deep Learning-based Label-Free Virtual HER2 Immunohistochemical Staining of Breast Tissue
ByMahi Sharma November 1, 2022November 2, 2022
Evident with the increasing cost and laborious work of diagnosis of cancer, using the gold standard Immunohistochemical (IHC) staining of tissues. Researchers from the University of California, Los Angeles, described a label-free virtual HER2 IHC staining based on a deep learning method. Introduction Immunohistochemical staining of cancer tissues, such as the HER2 biomarker, is widely…
Read More Researchers Introduced a Deep Learning-based Label-Free Virtual HER2 Immunohistochemical Staining of Breast Tissue
AI | Bioinformatics | Cancer Research | Deep Learning | News | Paper Summary | Precision Medicine | Trending
Artificial Intelligence Strategies For Multimodal Fusion – A Path Towards Precision Oncology
ByShwetha S October 31, 2022November 9, 2022
Cancer is a significant threat worldwide. In a study published in ACS Cancer, authors Bray et al. stated that cancer may overtake cardiovascular disease as the leading cause of premature death worldwide over the course of this century. Cancer biomarkers are the biological molecules produced by the tumor in a person; this helps characterize the…
Read More Artificial Intelligence Strategies For Multimodal Fusion – A Path Towards Precision Oncology
Bioinformatics | Cancer Research | Computational Models | Neural Network | News | Paper Summary | Precision Medicine | Trending
PRECILY – A Deep Neural Network-based Cancer Drug Response Predictor
ByShwetha S October 29, 2022October 29, 2022
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 tumors to various drugs using gene expression data and anti-cancer drug descriptors. Personalized cancer medicine or precision medicine is the need of the hour for better treatment of highly convoluted diseases…
Read More PRECILY – A Deep Neural Network-based Cancer Drug Response Predictor
Bioinformatics | Chronic Diseases | Machine Learning | Metagenomics | News | NGS | Paper Summary
Accurate Sepsis Diagnosis using Integrated Host-Microbe Plasma Metagenomics Profiling
ByMahi Sharma October 28, 2022October 28, 2022
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 by the National Heart, Lung, and Blood Institute was conducted at the University of California, San Francisco, USA, to apply an integrated host-microbe metagenomics approach to accurately diagnose potential sepsis in…
Read More Accurate Sepsis Diagnosis using Integrated Host-Microbe Plasma Metagenomics Profiling
Bioinformatics | Covid-19 News | Machine Learning | News | Paper Summary | SARS-CoV-2 | Structural Biology | Trending
Synergistic Protein Modeling Using AlphaFold and Density Maps Improves Structure Prediction Accuracy
ByShwetha S October 27, 2022October 27, 2022
A team of researchers led by Thomas Terwilliger from the New Mexico Consortium developed a procedure where the AlphaFold structure prediction models can be automatically rebuilt based on density maps. These models might, therefore, be used as templates for generating new AlphaFold models in the future. Machine learning algorithms are widely implicated in the prediction…
Read More Synergistic Protein Modeling Using AlphaFold and Density Maps Improves Structure Prediction Accuracy
Bioinformatics | News | Paper Summary | Trending
Researchers Find Clues to Protecting Crops from Blast Disease by Gaining Insights into Plant Host-Pathogen Interaction
ByCBIRT October 26, 2022October 26, 2022
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 the Banfield group at the John Innes Centre and collaborators have elucidated how rice blast fungus ZiF (Zinc finger) effectors bind a conserved Exo70 interface to manipulate plant exocytosis. Introduction Throughout…
Read More Researchers Find Clues to Protecting Crops from Blast Disease by Gaining Insights into Plant Host-Pathogen Interaction
Bioinformatics | Infectious Diseases | Neural Network | News | Paper Summary | Trending
Data Dimensionality Reduction Promotes Stage-specific Malaria Detection Based on Neural Networks
ByMahi Sharma October 25, 2022October 25, 2022
Owing to the increase in malaria infections and morbidities associated with it, an upgradation of diagnostics gold standard procedures can help elevate the disease burden. MTA-BME Morpho-dynamics Research Group from Budapest has integrated neural networks (NN), reducing the data dimension to address the limitations. High speeding the classification of RBCs (red blood cells) increases the…
Read More Data Dimensionality Reduction Promotes Stage-specific Malaria Detection Based on Neural Networks
AI | Bioinformatics | Cancer Research | Chronic Diseases | Drug Discovery | Machine Learning | News | Paper Summary | Precision Medicine | Trending
A Novel Machine Learning Method for Classifying Macrophages Could Facilitate the Development of Personalized Treatments for Multiple Diseases
ByShwetha S October 24, 2022October 22, 2026
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 shown that this technique is powerful for analyzing macrophage metabolism and classification. The Two-photon fluorescence lifetime imaging microscopy (2P-FLIM) is a non-invasive imaging technique that aids in visualizing cellular metabolism by…
Read More A Novel Machine Learning Method for Classifying Macrophages Could Facilitate the Development of Personalized Treatments for Multiple Diseases
Bioinformatics | News | Paper Summary | Sequencing | Trending
Genomic Insights into the Physiology of an Iconic Unculturable Rumen Bacterium ‘Quinella’
ByMahi Sharma October 23, 2022October 23, 2022
The iconic bacterial genus from sheep rumen ‘Quinella’ has been the center of bacterial taxonomy for various reasons. The research group from Massey University, New Zealand, and the National University of Singapore have deciphered the genomic insights using metagenomic sequencing. The analysis provided observations into taxonomic diversity and assess genetic data for the physiological understanding…
Read More Genomic Insights into the Physiology of an Iconic Unculturable Rumen Bacterium ‘Quinella’
AI | Bioinformatics | Computational Models | Deep Learning | Health | News | Paper Summary | Trending
Artificial Intelligence Accurately Predicts Patient’s Race from Medical Images – Can Lead to Unintentional Bias, Warns Scientists
ByShwetha S October 22, 2022October 22, 2022
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 images like X-rays, CT scans, and mammograms, even when the images were heavily altered, cropped, or noised. Studies have shown that AI deep learning models mimic the unconscious racial bias and…
Read More Artificial Intelligence Accurately Predicts Patient’s Race from Medical Images – Can Lead to Unintentional Bias, Warns Scientists
Bioinformatics | Health | News | Paper Summary | Trending
Novel EEG Phenotyping to Identify Neurological Disease from Sleep Brainwaves
ByMahi Sharma October 21, 2022October 21, 2022
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 neurologically diseased subjects. The approach provides fingerprint identification unique to each individual and identifies the potential for neurodegenerative disease phenotyping and biomarker identification. Introduction Traditionally, the identification of brainwaves in the…
Read More Novel EEG Phenotyping to Identify Neurological Disease from Sleep Brainwaves
AI | Bioinformatics | Cancer Research | Drug Discovery | Machine Learning | News | Paper Summary | Precision Medicine | Trending
Machine Learning Model ‘CODE-AE’ Predicts Personalized Cancer Drug Response Using Cell Line Data
ByShwetha S October 20, 2022October 22, 2026
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 capable of predicting the drug response elicited in a patient from a neural network model trained using cell-line data, thereby suggesting the model’s potential application in personalized medicine. Omics profiling has…
Read More Machine Learning Model ‘CODE-AE’ Predicts Personalized Cancer Drug Response Using Cell Line Data
Bioinformatics | Drug Discovery | News | Paper Summary
SQUID: A New Generative Model for Shape-Conditioned Generation of 3D Molecules for Structure-Based Drug Design
ByMahi Sharma October 19, 2022January 27, 2024
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 in 3D conformation. The team has successfully introduced equivariant deep working models to challenge current 2D generative models. Introduction Computer-aided drug design, CADD, has been reformed by integrating generative models. CADD…
Read More SQUID: A New Generative Model for Shape-Conditioned Generation of 3D Molecules for Structure-Based Drug Design
Bioinformatics | Cancer Research | COVID-19 | GWAS | Health | News | NGS | Paper Summary | RNA-Seq | Transcriptomics | Trending
Single-cell RNA Sequencing and GWAS Data Integration Discover New Disease Cell Types and Pathways
ByShwetha S October 18, 2022October 18, 2022
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 to different cell types and physiological processes. This is done by integrating Genome-Wide Association Studies summary statistics, epigenomic data, and single-cell RNA (scRNAseq) sequence data from multiple tissues, cells, diseases, and…
Read More Single-cell RNA Sequencing and GWAS Data Integration Discover New Disease Cell Types and Pathways
Bioinformatics | Cancer Research | Computational Models | News | Paper Summary | RNA-Seq | Transcriptomics | Trending
Attention-based Multi-view Graph Collaborative Learning Model ‘stMVC’ to Decipher Tumor Heterogeneity in Spatial Transcriptomics Data
ByMahi Sharma October 17, 2022October 16, 2022
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 on their composition. A collaborative team of researchers from China has introduced a multi-view graph collaborative model, ‘stMVC’ (Spatial Transcriptomics data analysis by Multiple View Collaborative-learning), to analyze SRT data and elucidate tissue heterogeneity to…
Read More Attention-based Multi-view Graph Collaborative Learning Model ‘stMVC’ to Decipher Tumor Heterogeneity in Spatial Transcriptomics Data
Bioinformatics | News | Paper Summary | Structural Biology | Trending
Demystifying Large Protein Complex Structures Using AlphaFold and Monte Carlo Tree Search
ByShwetha S October 16, 2022October 16, 2022
Researchers from Stockholm University, Sweden, have developed a novel bioinformatics pipeline to predict the structure of large protein molecules, such as the nuclear pore or the 26S proteasome complex, using AlphaFold and Monte Carlo Tree Search. A protein complex is a group of two or more polypeptide chains associated together. These biological entities play a…
Read More Demystifying Large Protein Complex Structures Using AlphaFold and Monte Carlo Tree Search
Bioinformatics | Drug Discovery | Health | News | Paper Summary | Trending
DrugRep: An Automated and Parameter-Free Virtual Screening Tool for Drug Repurposing
ByMahi Sharma October 15, 2022October 22, 2026
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 and ligand-based methods. Being freely available, it provides the unstinted potential for repurposing and investing in current pharmacology. Historically, introducing novel drugs bears challenges in terms of exploring and introducing them…
Read More DrugRep: An Automated and Parameter-Free Virtual Screening Tool for Drug Repurposing
Big Data | Bioinformatics | Health | Machine Learning | News | Paper Summary | Trending
Insurance Claim Data and Machine Learning Aids in the Early Detection of Autism Spectrum Disorder
ByShwetha S October 14, 2022October 14, 2022
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 age, between 18 to 30 months. Such early detection can vastly help both the patients and the clinicians to improve treatment outcomes. The authors define Autism Spectrum Disorder (ASD) as a…
Read More Insurance Claim Data and Machine Learning Aids in the Early Detection of Autism Spectrum Disorder
Bioinformatics | Covid-19 News | Drug Discovery | News | Paper Summary | SARS-CoV-2 | Trending | Virus
A Systematic Proteome-scale Contactome Map Reveals How SARS-CoV-2 Communicates with Human Cells
ByMahi Sharma October 13, 2022October 22, 2026
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 in research by systematically identifying protein interaction contacts between humans and the sars-cov-2 proteome. The team successfully evaluated the ‘contactome theory’, associating the host genome with morbidity and the COVID-19 community…
Read More A Systematic Proteome-scale Contactome Map Reveals How SARS-CoV-2 Communicates with Human Cells
Bioinformatics | Machine Learning | Neural Network | News | Paper Summary | Trending
KAGE – A Fast Alignment-free Graph-based Genotyper for SNPs and Short Indels
ByShwetha S October 12, 2022October 12, 2022
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 word-based approach to genotype variants in a shorter duration, higher accuracy, and less memory. Genotyping refers to the process of detecting the genotype (genetic makeup) of an individual using biological techniques…
Read More KAGE – A Fast Alignment-free Graph-based Genotyper for SNPs and Short Indels
AI | Bioinformatics | Deep Learning | News | Paper Summary
Predicting Genome-Wide Chromatin Loop using Deep Learning Model ‘DLoopCaller’
ByCBIRT October 11, 2022October 11, 2022
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 new era in genomic medicine. Researchers from Shanghai, China, have presented DLoopCaller – a deep learning approach to predict chromatin architecture to identify gene regulation down to transcription factor. Chromatin is…
Read More Predicting Genome-Wide Chromatin Loop using Deep Learning Model ‘DLoopCaller’
Bioinformatics | Cancer Research | Computational Models | Health | Machine Learning | News | Paper Summary | Trending
A Novel Semi-Supervised Machine Learning Model for Patch-based Breast Cancer Classification
ByShwetha S October 10, 2022October 9, 2022
Researchers from Tartu University have put forth a semi-supervised machine learning framework to detect invasive ductal carcinoma using a small amount of labeled breast cancer histological data. Breast cancer is one of the most common cancers. According to the world health organization (WHO), nearly 2.3 million women worldwide have been affected with breast cancer, with…
Read More A Novel Semi-Supervised Machine Learning Model for Patch-based Breast Cancer Classification
AI | Bioinformatics | Deep Learning | News | Paper Summary | Trending
Explainable AI – Deep Learning Models: Black Box to Emerging Genomics Research
ByMahi Sharma October 9, 2022October 9, 2022
Deep learning extensively affects studying genetics and the breakthrough research associated with them. The study focuses on understanding the building of complex models rather than complex datasets using model interpretations in Explainable Artificial Intelligence (xAI). This helps in understanding the utility of complex models to decipher biological datasets. Artificial intelligence-based deep learning models are known…
Read More Explainable AI – Deep Learning Models: Black Box to Emerging Genomics Research
Bioinformatics | Genomics | GWAS | News | Paper Summary | Trending
A New Study Reveals the Landscape and Evolution of Nuclear-Mitochondrial Segments
ByShwetha S October 8, 2022October 8, 2022
Researchers from Cambridge University have reported the presence of nuclear-mitochondrial segments (NUMT) in a sample population of 66,083 people with 12,509 cancer samples. Whole genome sequencing (WGS) of the samples observed de novo NUMT of one in every 10^4 births and one in every 10^3 cancers, indicating that DNA translocation is a continuing process. Endosymbiosis…
Read More A New Study Reveals the Landscape and Evolution of Nuclear-Mitochondrial Segments
Big Data | Bioinformatics | Drug Discovery | Machine Learning | Neural Network | News | Paper Summary | RNA-Seq | Trending
HAL-X: A Novel Clustering Algorithm for Rapid Single-Cell Data Analysis for Drug Discovery
ByMahi Sharma October 7, 2022October 22, 2026
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 the generation of multiple-clustering for in-depth analysis of high-dimensional data. The future directions of algorithms are extremely promising in understanding disease, disease progression, and drug discovery. Throughout the years, clustering has…
Read More HAL-X: A Novel Clustering Algorithm for Rapid Single-Cell Data Analysis for Drug Discovery
AI | Bioinformatics | Chronic Diseases | Health | Machine Learning | News | Trending
Unraveling Diseases with Data – Machine Learning Helps Identify New Nonlinear Progression Patterns in Neurodegenerative Disorders
ByShwetha S October 6, 2022November 24, 2023
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 clinical trials and discover mechanisms behind the disease. The study also highlights that the model can be extrapolated to other neurodegenerative disorders, like Alzheimer’s and Parkinson’s, to trace disease patterns. Neurodegenerative diseases…
Read More Unraveling Diseases with Data – Machine Learning Helps Identify New Nonlinear Progression Patterns in Neurodegenerative Disorders
AMR Alert | Antibiotic Resistance | Bioinformatics | Health | Infectious Diseases | Metagenomics | News | Paper Summary | Trending
Understanding the Population Dynamics for AMR Burden due to Carbapenemase-producing Enterobacteriaceae in Gut Microbiome
ByMahi Sharma October 5, 2022January 8, 2024
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 to understand microbiome ecology within the population suggests visible shifts in microbial pathways assisting in the colonization of Enterobacteriaceae favoring CPE (Carbapenemase-producing Enterobacteriaceae ) infections. The study provides imperative insight into…
Read More Understanding the Population Dynamics for AMR Burden due to Carbapenemase-producing Enterobacteriaceae in Gut Microbiome
Bioinformatics | Deep Learning | Machine Learning | News | Paper Summary | Tools | Trending
Researchers Identified Deep Learning Tools as the Top Performers for Predicting Long Non-coding RNA
BySrishti Sharma October 3, 2022October 3, 2022
New RNA transcripts have been discovered as a result of the growing amount of transcriptomic data. Bioinformatic tool developers have had difficulty separating long non-coding RNA (lncRNA) from protein-coding messenger RNA (mRNA). Currently, tools implementing deep learning architectures have been developed to accomplish this task, but their potential to discover sequence features and their interactions…
Read More Researchers Identified Deep Learning Tools as the Top Performers for Predicting Long Non-coding RNA
Bioinformatics | Data Science | News | NGS | OMICS | Paper Summary | RNA-Seq | Sequencing | Trending
In a Benchmark Study, Scientists Investigated the Integration of Temporal Sequencing Modalities for Trajectory Inference and Disease Prediction
ByMahi Sharma October 2, 2022October 1, 2022
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 School of Medicine benchmark study addressed gaps in capturing temporal changes in a single-cell state. Interpretation of dynamic phenotypes using ten datasets spanning different biological environments at three distinct temporal stages….
Read More In a Benchmark Study, Scientists Investigated the Integration of Temporal Sequencing Modalities for Trajectory Inference and Disease Prediction
AI | Bioinformatics | Cancer Research | Machine Learning | News | Paper Summary | Tools | Trending
New AI Tool ‘SigProfilerExtractor’ Identifies Mutational Signature Linked To Tobacco Smoking and Bladder Cancer
BySrishti Sharma September 30, 2022September 30, 2022
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 University of California San Diego School of Medicine and published in the journal Cell Genomics. The study may help researchers determine what environmental factors could cause cancer in certain patients, such…
Read More New AI Tool ‘SigProfilerExtractor’ Identifies Mutational Signature Linked To Tobacco Smoking and Bladder Cancer
Bioinformatics | Cancer Research | Drug Discovery | Machine Learning | News | Paper Summary | Trending
Eliminating the Confounder Bias – A Radical Approach for Better Identification of Cancer Drug Targets
ByShwetha S September 29, 2022October 22, 2026
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 progression. Cancer is one of the deadliest diseases worldwide. According to the World Health Organization (WHO), cancer has claimed the lives of nearly 10 million people in 2020. Mutations in the…
Read More Eliminating the Confounder Bias – A Radical Approach for Better Identification of Cancer Drug Targets
Bioinformatics | Metagenomics | News | Paper Summary | Sequencing | Tools | Trending
iNAP: An Integrated Network Analysis Pipeline for Microbiome Studies in Complex Ecosystems
ByMahi Sharma September 28, 2022September 28, 2022
Microbial network analysis is an acceptable approach to investigating microbiome and metagenomic datasets and finding insights into a complex ecosystem. Ye Deng et al. introduced an integrated pipeline, iNAP, for network construction and visualization to help researchers understand microbial ecology without prior knowledge of bioinformatics or statistical programming skills. Understanding and deducing information from microbial…
Read More iNAP: An Integrated Network Analysis Pipeline for Microbiome Studies in Complex Ecosystems
AMR Alert | Bioinformatics | Infectious Diseases | Machine Learning | Metagenomics | News | NGS | Paper Summary | Trending
Scientists Investigated Microbial Communities and Resistomes in Relation to Interconnected Humans, Soil, and Livestock
BySrishti Sharma September 27, 2022September 27, 2022
Antimicrobial resistance (AMR) may be reservoired in intensive livestock farms, posing a threat to surrounding communities. The gut microbiome of livestock, workers, and their households, as well as microbial communities in carcasses and soil, were investigated using shotgun metagenome sequencing, machine learning (ML), and culture-based methods at a poultry farm in China. In this study,…
Read More Scientists Investigated Microbial Communities and Resistomes in Relation to Interconnected Humans, Soil, and Livestock
Bioinformatics | Cancer Research | News | NGS | Paper Summary | Sequencing | Trending
Mathematical Modeling Bridges Chromatin Architecture with Potential in Genome Medicine
ByMahi Sharma September 26, 2022September 26, 2022
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 genome. Understanding how a cell is organized could help biologists develop treatments that halt cancer and other diseases. The kinetics of high-order chromatin composition is known to play a role in…
Read More Mathematical Modeling Bridges Chromatin Architecture with Potential in Genome Medicine
AI | Bioinformatics | COVID-19 | Drug Discovery | News | Structural Biology | Tools | Trending
Accelerating the Discovery of New Drugs with AI-based Screening Methods
ByDr. Tamanna Anwar September 25, 2022September 29, 2022
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 protein interactions. Drug discovery has become a major bottleneck in modern medicine. Researchers have developed several methods to speed up the process in recent years, such as high-throughput screening (HTS). HTS…
Read More Accelerating the Discovery of New Drugs with AI-based Screening Methods
AI | Bioinformatics | Deep Learning | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Trending
Meet “ProteinMPNN,” A Robust Deep Learning-based Protein Sequence Design Algorithm
BySrishti Sharma September 24, 2022October 22, 2026
Predicting protein structure has been revolutionized by machine learning over the past two years. A similar breakthrough in protein design has now been reported in the journal Science. The researchers from the Baker lab at the University of Washington demonstrate that machine learning makes the design of proteins much more accurate and faster with a…
Read More Meet “ProteinMPNN,” A Robust Deep Learning-based Protein Sequence Design Algorithm
Bioinformatics | Metagenomics | News | NGS | Paper Summary | Sequencing | Trending
Microbiome Data Analysis using Differential Abundance Methods – A Benchmark Study
BySrishti Sharma September 22, 2022September 22, 2022
In order to perform an extensive benchmarking of the known tools for differential abundance analysis, the researchers from the University of Padova used a simulator of microbiome data to create a simulation framework based on microbiome data. This is the first step towards the development of a robust, reliable, and fair simulation framework that will…
Read More Microbiome Data Analysis using Differential Abundance Methods – A Benchmark Study
AI | Bioinformatics | Health | News | Trending
CheXzero: A Tool to Identify Pathologies from Unannotated Chest X-ray Images Using Self-supervised Learning
ByDr. Tamanna Anwar September 21, 2022January 26, 2023
The new tool “CheXzero” improves clinical AI design by overcoming the major hurdle of labeling datasets for model training. Scientists at Harvard Medical School and Stanford University have developed an artificial intelligence diagnostic tool that can detect diseases directly from natural language descriptions of chest X-rays. This is a major step forward in clinical AI…
Read More CheXzero: A Tool to Identify Pathologies from Unannotated Chest X-ray Images Using Self-supervised Learning
Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Tools | Trending
DeepFold: A Fast and Accurate Method for Ab Initio Protein Structure Prediction using Deep Learning Potentials
BySrishti Sharma September 20, 2022January 26, 2023
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 of recent progress in protein structure prediction, it is still necessary to improve the accuracy of models for proteins lacking sequence and/or structure homologs. The DeepFold program uses multi-task deep residual…
Read More DeepFold: A Fast and Accurate Method for Ab Initio Protein Structure Prediction using Deep Learning Potentials
Bioinformatics | News | Structural Biology | Trending
Vanderbilt University Researchers Suggest a New Mechanism for the Lipid Transporter
ByDr. Tamanna Anwar September 19, 2022September 18, 2022
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) are a type of protein that helps transport cholesterol throughout the body. HDL particles have a higher concentration of cholesterol than low-density lipoproteins. The HDL cholesterol or “good cholesterol” carries…
Read More Vanderbilt University Researchers Suggest a New Mechanism for the Lipid Transporter

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