Bioinformatics | Computational Models | Health | News | Paper Summary | Precision Medicine | Trending

MIT Researchers Used Large Language Models to Decode Clinical Health Records in Few Shots
ByRiya Vishwakarma December 7, 2022December 25, 2023

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 of electronic health records aims to enhance and simplify healthcare. Beyond the purview of clinical trials, the vast quantity of data in these now-digital records might be utilized to address…

Read More MIT Researchers Used Large Language Models to Decode Clinical Health Records in Few Shots
Bioinformatics | Health | News | Paper Summary | Tools | Trending

UCL Researchers Unraveled the Hidden Patterns Involved in Patients with Multimorbidities
ByShwetha S December 6, 2022December 6, 2022

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 use the study findings and interactive online tools to prevent and detect comorbid conditions. In contrast, biomedical researchers and pharmaceutical manufacturers can use them to provide lead compounds targeting common or…

Read More UCL Researchers Unraveled the Hidden Patterns Involved in Patients with Multimorbidities
Bioinformatics | Metabolomics | News | NGS | OMICS | Sequencing | Trending

A Multi-Omics Approach to Earth’s Microbiomes Project Demonstrates Microbial and Metabolite Diversity
ByRiya Vishwakarma December 5, 2022December 5, 2022

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 in DNA sequencing, the establishment of general conclusions regarding microbial life on Earth is hampered by the absence of standardized techniques and shared analytical frameworks. Researchers at the University of California San…

Read More A Multi-Omics Approach to Earth’s Microbiomes Project Demonstrates Microbial and Metabolite Diversity
AI | Bioinformatics | COVID-19 | News | Paper Summary | SARS-CoV-2 | Trending

Meet GenSLMs, A Genome-Level AI Model That Helps Track COVID Variants’ Evolution
ByShwetha S December 4, 2022December 4, 2022

Argonne National Laboratory researchers, together with partners from six different universities, NVIDIA, and Cerebras Inc., have collaborated to create GenSLMs, that learn the evolutionary landscape of the SARS-CoV2 genome using large language models (LLMs) resources. The Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research in 2022 has been awarded to GenSLMs. Rapid sequencing…

Read More Meet GenSLMs, A Genome-Level AI Model That Helps Track COVID Variants’ Evolution
AI | Big Data | Bioinformatics | Genomics | Health | News | OMICS | Precision Medicine | Trending

Amazon’s Big Bet On Bioinformatics – Introduces Amazon OMICS – A Comprehensive Service for Storing, Querying, and Analyzing Genomic and Biological Big Data
ByDr. Tamanna Anwar December 3, 2022December 3, 2022

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 scale. It offers fast, secure, and cost-effective storage, access, and analysis of large datasets, allowing customers to gain insights from their data and accelerate research quickly. Amazon Omics is designed to…

Read More Amazon’s Big Bet On Bioinformatics – Introduces Amazon OMICS – A Comprehensive Service for Storing, Querying, and Analyzing Genomic and Biological Big Data
Bioinformatics | Cancer Research | Machine Learning | News | Paper Summary | Trending

A New Machine Learning Algorithm Classifies Sinonasal Tumors Based on DNA Methylation
ByRiya Vishwakarma December 1, 2022December 1, 2022

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 information was utilized to thoroughly examine the molecular patterns of sinonasal undifferentiated carcinomas (SNUCs), which were inaccurately defined and contested in earlier investigations. Sinonasal tumors have a variety of histopathologies and…

Read More A New Machine Learning Algorithm Classifies Sinonasal Tumors Based on DNA Methylation
Bioinformatics | Cancer Research | News | NGS | OMICS | Paper Summary | RNA-Seq | Trending

Scientists Decipher the Molecular Subsets Involved in Brain Metastases of Melanoma
ByShwetha S November 30, 2022November 30, 2022

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 location, it was found that the expression of E-cadherin (Ecad) or Nerve Growth Factor Receptor (NGFR) progresses tumors into proliferative and therapy-resistant states. The investigation of MAPK inhibitor-naive and refractory melanoma…

Read More Scientists Decipher the Molecular Subsets Involved in Brain Metastases of Melanoma
Bioinformatics | News | NGS | Paper Summary | RNA-Seq | Sequencing | Tools | Trending

RNAlysis: a Gateway into RNA Sequencing Data Analysis for Less Computer-savvy Researchers
ByRiya Vishwakarma November 29, 2022November 29, 2022

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 challenges are even more difficult for researchers who are not accustomed to writing computer code because the bulk of the analysis tools accessible demand programming knowledge. A customizable Python-based analysis program…

Read More RNAlysis: a Gateway into RNA Sequencing Data Analysis for Less Computer-savvy Researchers
Bioinformatics | Computational Models | Deep Learning | Machine Learning | News | Paper Summary | Proteomics | Trending

Meet AlphaPeptDeep: a Deep Learning Framework for Predicting Peptide Properties from Sequences
ByShwetha S November 28, 2022November 28, 2022

A research team led by Professor Matthias Mann from the Max Planck Institute of Biochemistry has developed AlphaPeptDeep. AlphaPeptDeep is a Python framework built on the PyTorch deep learning library that can learn and predict peptide properties. AlphaPeptDeep additionally includes a plug-in capability that allows non-experts to develop models with just a few lines of…

Read More Meet AlphaPeptDeep: a Deep Learning Framework for Predicting Peptide Properties from Sequences
AI | Bioinformatics | Deep Learning | Neural Network | News | Paper Summary | Trending

ExpressionGAN: Generating Long Designer DNA Sequences On-Demand With Deep Learning
ByRiya Vishwakarma November 27, 2022January 20, 2024

A new deep learning method developed by a team of researchers at Chalmers can generate regulatory DNA sequences that control gene expression in a gene-specific manner. Despite significant sequence divergence from natural DNA, in vivo measurements reveal that 57% of the synthetic sequences with high expression levels outperform the expression levels of the correspondingly highly…

Read More ExpressionGAN: Generating Long Designer DNA Sequences On-Demand With Deep Learning
Bioinformatics | Infectious Diseases | Metagenomics | News | NGS | Paper Summary | Trending

Enhancing the Comprehensive Diagnosis of Neonatal Infectious Diseases Through Metagenomic Next-Generation Sequencing
ByShwetha S November 26, 2022November 26, 2022

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 various bodily fluids and blood samples extracted from newborns. Researchers also performed a local polynomial regression fitting analysis, which revealed that the best time for detecting mNGS was 1 to 3…

Read More Enhancing the Comprehensive Diagnosis of Neonatal Infectious Diseases Through Metagenomic Next-Generation Sequencing
Bioinformatics | Chronic Diseases | Computational Models | Health | Machine Learning | News | Paper Summary | Trending

Scientists Develop Novel Machine Learning Models to Predict Comorbidities at an Early Stage of Type 2 Diabetes Mellitus
ByRiya Vishwakarma November 25, 2022November 25, 2022

Researchers at AstraZeneca and Ono Pharmaceuticals sought to create a model that could predict the likelihood that individuals with Type 2 Diabetes Mellitus (T2DM) who had no prior history of CKD or CVDs would develop CKD/HF. Using the prediction model, it would be possible to identify individuals with T2DM who are at a high risk…

Read More Scientists Develop Novel Machine Learning Models to Predict Comorbidities at an Early Stage of Type 2 Diabetes Mellitus
Antibiotic Resistance | Bioinformatics | News | Paper Summary | Trending

Scientists Created a High-Resolution Global Map of Clinically Relevant Antimicrobial Resistance Genes
ByShwetha S November 24, 2022November 29, 2022

Researchers from the University of Antwerp screened 17939 assembled metagenomic samples from 21 different biomes, varying in sequencing quality and depth, over 46 countries, across 6 continents, for a period of 14 years (2005-2019) for clinically crucial antibiotic resistance genes (ARGs) commonly found in human biomes, anthropogenic biomes, and natural biomes such as freshwater, marine,…

Read More Scientists Created a High-Resolution Global Map of Clinically Relevant Antimicrobial Resistance Genes
Big Data | Bioinformatics | News | NGS | Paper Summary | RNA-Seq | Tools | Transcriptomics | Trending

Multi-platform Universal Single-cell RNAseq Data Processing Pipeline – UniverSC
ByRiya Vishwakarma November 23, 2022November 23, 2022

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 works with different single-cell technologies, via a graphical user interface, operable on macOS, Windows, and Linux Ubuntu, eliminating data processing for single-cell RNAseq (scRNAseq) analysis for researchers who are naive to…

Read More Multi-platform Universal Single-cell RNAseq Data Processing Pipeline – UniverSC
AI | Bioinformatics | Cancer Research | Machine Learning | News | Trending

Scientists Developed a Novel AI Blood Test ‘DELFI’ for Early Detection of Liver Cancer
ByDr. Tamanna Anwar November 22, 2022November 22, 2022

Johns Hopkins Kimmel Cancer Center researchers developed and used artificial intelligence blood testing technology. The new blood testing technology detected liver cancer in more than 80% of participants in a study of 724 people. The technology, which uses a machine learning algorithm to analyze blood samples, showed promise in a previous study for detecting lung…

Read More Scientists Developed a Novel AI Blood Test ‘DELFI’ for Early Detection of Liver Cancer
AI | Bioinformatics | News | Paper Summary | Structural Biology | Trending

FASSO: An AlphaFold-based Method Combines Sequence and Structure Orthology to Assign Functional Annotations to Proteins
ByRiya Vishwakarma November 21, 2022November 21, 2022

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 of how these structures relate to function. The researchers from USDA-ARS describe a methodology “Functional Annotations using Sequence and Structure Orthology (FASSO),” which takes advantage of AlphaFold along with sequence and…

Read More FASSO: An AlphaFold-based Method Combines Sequence and Structure Orthology to Assign Functional Annotations to Proteins
AI | Algorithm | Bioinformatics | Chronic Diseases | Health | News | Trending

Smartwatch ECG Signals Transformed into Diagnostic Tools for Heart Failure using Artificial Intelligence
ByDr. Tamanna Anwar November 20, 2022November 23, 2022

A new study published by researchers at the Mayo Clinic has shown that a smartwatch ECG can accurately detect heart failure in nonclinical environments. This is a significant breakthrough because it shows that heart failure can now be detected earlier and more effectively. The research published in Nature Medicine reports a couple of health technology…

Read More Smartwatch ECG Signals Transformed into Diagnostic Tools for Heart Failure using Artificial Intelligence
Bioinformatics | News | Paper Summary | Statistics | Trending

Functional Connectivity MultiVariate Pattern Analysis – A Novel Method for the Analysis of Human Connectome
ByShwetha S November 19, 2022November 29, 2022

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). The novel technique uses classic MVPA to evaluate each voxel in a three-dimensional space and traces functional connections to the brain. Monte Carlo simulations are also used in the study to…

Read More Functional Connectivity MultiVariate Pattern Analysis – A Novel Method for the Analysis of Human Connectome
Bioinformatics | Cancer Research | Drug Discovery | News | NGS | OMICS | Paper Summary | Precision Medicine | Trending

A Bioinformatics Roadmap for Drug Prioritization from Cancer Genomics Data
ByRiya Vishwakarma November 18, 2022October 22, 2026

Cancer is a complicated disease brought on by the interaction of various informational layers. Tumor origin, the appearance of genomic and transcriptomic variations, or interactions with the microenvironment are all factors that contribute to the difficulty of treating tumors. With reference to the types of tumor heterogeneity and the accessible data from next-generation sequencing, the…

Read More A Bioinformatics Roadmap for Drug Prioritization from Cancer Genomics Data
Big Data | Bioinformatics | Computational Models | Genomics | GWAS | News | Paper Summary | Trending

CLIMB – A New Statistical Method for Improved Large Scale Genomic Data Analysis
ByShwetha S November 17, 2022November 29, 2022

Researchers from Penn State University present CLIMB (Composite Likelihood eMpirical Bayes), a statistical tool that discovers patterns of condition specificity in a given genomic data. It also provides a generic framework for a variety of investigations, such as aggregating genomic features with comparable condition-specific patterns. CLIMB outperforms the existing options in statistical precision while capturing…

Read More CLIMB – A New Statistical Method for Improved Large Scale Genomic Data Analysis
Bioinformatics | Cancer Research | Deep Learning | Drug Discovery | News | Paper Summary | Precision Medicine | Trending

Researchers Introduce a Deep Learning Platform ‘OrganoID’ to Track Single-organoid Dynamics for Drug Exploration
ByMahi Sharma November 16, 2022October 22, 2026

Recent research conducted by the research group of Savas Tay at the University of Chicago, Illinois, USA, introduced a deep learning platform, OrganoID to analyze and interpret the organoid models for personalized drug screening. The team has interpreted results and validated the platform using pancreatic cancer organoid images, revolutionizing biomedicine. Introduction Organoid research has…

Read More Researchers Introduce a Deep Learning Platform ‘OrganoID’ to Track Single-organoid Dynamics for Drug Exploration
Bioinformatics | Genomics | News | NGS | Paper Summary | Sequencing | Trending

Scientists Unveil High-Resolution Reference Genome of Nile Rat – A Promising Animal Model for Diabetes Research
ByShwetha S November 13, 2022November 13, 2022

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 gene annotations deciphering the Nile Rat (Arvicanthis niloticus) as a carbohydrate-sensitive model for diabetes research. An animal model is a living, genetically engineered organism used for research and investigating human diseases….

Read More Scientists Unveil High-Resolution Reference Genome of Nile Rat – A Promising Animal Model for Diabetes Research
Bioinformatics | Cancer Research | Genomics | News | NGS | Paper Summary | RNA-Seq | Sequencing | Trending

A Novel CRISPR-based Technique ‘MACHETE’ Investigates Copy Number Alterations in Cancer Genome
ByMahi Sharma November 12, 2022January 10, 2024

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 the laboratory using the pancreatic and melanoma cancer mouse models. The CRISPR-based method revealed clinically relevant observations into the multifaceted nature of 9p21.3 ommissions that contribute to up to 15% of…

Read More A Novel CRISPR-based Technique ‘MACHETE’ Investigates Copy Number Alterations in Cancer Genome
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
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 | 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 | 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
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

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