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Bioinformatics and computational biology news: new methods, tools and findings from recent research, explained clearly.

AI | Bioinformatics | Computational Models | Disease Diagnosis | Health | Machine Learning | News | Trending
New Study Aims to use Machine Learning to Explore the Surprising Relationship Between Oral Infections and Cardiovascular Disease
ByDr. Tamanna Anwar March 21, 2023March 21, 2023
According to a new study presented at the 52nd Annual Meeting & Exhibition of the AADOCR, held in conjunction with the 47th Annual Meeting of the CADR, the researchers aim to develop a machine learning model for predicting cardiovascular disease using indicators of oral infections. The researchers believe that by using Machine learning, the relationship…
Read More New Study Aims to use Machine Learning to Explore the Surprising Relationship Between Oral Infections and Cardiovascular Disease
AI | Bioinformatics | Deep Learning | Disease Diagnosis | News | Paper Summary | Trending
Exploring the Potential of DALL-E 2 for AI-driven Image Generation in Radiology
BySejal Saxena March 20, 2023March 20, 2023
In the field of radiology, generative models, notably DALL-E 2, have tremendous promise for image production and modification. Scientists have shown that DALL-E 2 has learned relevant x-ray picture representations and is able to produce new images from text descriptions, expand images beyond their initial borders, and delete elements. Despite limitations, the authors feel that…
Read More Exploring the Potential of DALL-E 2 for AI-driven Image Generation in Radiology
AI | Bioinformatics | Cancer Research | Deep Learning | Health | Neural Network | News | Paper Summary | Precision Medicine | Trending
The Future of Cancer Care: Explainable AI Detects Diagnostic Cells of Genetic AML Subtypes
ByBanhita Maitra March 19, 2023March 19, 2023
Scientists from Germany have developed SCEMILA, an inherently explainable AI tool for identifying diagnostic cells of acute myeloid leukemia (AML) subtypes. The authors find that the high-attention cells identified by SCEMILA coincide with cells labeled as diagnostically relevant by human experts. The model is trained based on single white blood cell images from digitized blood…
Read More The Future of Cancer Care: Explainable AI Detects Diagnostic Cells of Genetic AML Subtypes
AI | Bioinformatics | Neural Network | News | Paper Summary | Structural Biology | Tools | Trending
Meet PAthreader: A Powerful Tool for Protein Structure and Folding Pathway Prediction using Remote Homologs Recognition
BySejal Saxena March 18, 2023March 18, 2023
Scientists from the Zhejiang University of Technology, China, have proposed a new method, PAthreader, to improve the recognition accuracy of remote homologous structures by designing a three-track alignment between predicted distance profiles and structure profiles extracted from the PDB and AlphaFoldDB. As a result, AlphaFold2 performs better, and structural modeling is more precise. The results…
Read More Meet PAthreader: A Powerful Tool for Protein Structure and Folding Pathway Prediction using Remote Homologs Recognition
Bioinformatics | News | NGS | Statistics | Structural Biology | Trending
New Study Reveals Gene Mutation that Controls Pain Sensitivity
ByCBIRT March 17, 2023March 17, 2023
The experience of pain is complicated, subjective, and unique to each person. While some people have a high pain tolerance, others may regard even minor discomfort as excruciating pain. Pain affects over 1.5 billion people worldwide and costs more than $600 billion in the United States annually. Despite the availability of various pain relief medications,…
Read More New Study Reveals Gene Mutation that Controls Pain Sensitivity
AI | Bioinformatics | Machine Learning | News | Paper Summary | Proteomics | Trending
Pushing the Limits of Protein Detection: The Role of Machine Learning
ByBanhita Maitra March 16, 2023November 24, 2023
The detection of biomolecules at the nanoscale is of great significance in fundamental biology research, just as it is for biomedical investigations. The evolution of techniques for the detection and characterization of biomolecules has resulted in remarkable scale and resolution in terms of the size and mass of the molecules. Scientists from Germany have achieved…
Read More Pushing the Limits of Protein Detection: The Role of Machine Learning
Bioinformatics | Corona Virus | COVID-19 | Covid-19 News | News | Paper Summary | SARS-CoV-2 | Trending
New Study Shows Pan-variant mRNA-LNP T Cell Vaccine Proves Effective Against SARS-CoV-2 Beta
BySejal Saxena March 15, 2023March 15, 2023
Current COVID-19 vaccines induce neutralizing antibodies that can inhibit viral entry, but their efficiency decreases when new variations arise. On the basis of short peptide epitopes that stimulate CD8+ and CD4+ T cell responses, scientists have created a new mRNA-LNP (Lipid nanoparticle) vaccine called MIT-T-COVID. Researchers evaluated this novel vaccination on mice infected with the…
Read More New Study Shows Pan-variant mRNA-LNP T Cell Vaccine Proves Effective Against SARS-CoV-2 Beta
Cancer Research | Chemoinformatics | Drug Discovery | Machine Learning | News | Paper Summary | Trending
Bridging the Gap between Cheminformatics and Machine Learning to Investigate Androgen Receptor Antagonists in the Fight Against Prostate Cancer
ByBanhita Maitra March 14, 2023October 22, 2026
Researchers from Thailand perform a systematic cheminformatics analysis and machine learning modeling to study how human Androgen Receptors (AR) antagonists combat Prostate cancer, one of the leading causes of death in male cancer patients. Androgen receptor signaling drives the growth and prostate cancer progression. The authors perform the study on human AR antagonists from the…
Read More Bridging the Gap between Cheminformatics and Machine Learning to Investigate Androgen Receptor Antagonists in the Fight Against Prostate Cancer
AI | Antibiotic Resistance | Bioinformatics | Infectious Diseases | News | Paper Summary | Proteomics | Structural Biology | Trending
AI-Powered Structural Proteomics Unveils New Insights into Protein Complexes in Cells
BySejal Saxena March 13, 2023October 22, 2026
Molecular biology is being revolutionized by the application of artificial intelligence to simulate the structures of proteins and their complexes. Researchers utilized a combination of in-cell crosslinking mass spectroscopy and co-fractionation mass spectroscopy in order to find protein-protein interactions in Bacillus subtilis. With the help of AlphaFold-Multimer, the scientists predicted the structures of protein interactions,…
Read More AI-Powered Structural Proteomics Unveils New Insights into Protein Complexes in Cells
Bioinformatics | Metabolomics | News | Paper Summary | Proteomics | Tools | Trending
Scientists Introduce “MZmine3” for Processing Big Data to Identify Hidden Chemicals in Complex Mixtures
ByBanhita Maitra March 12, 2023March 12, 2023
Scientists from Prague have developed MZmine3, a scalable platform for the analysis of mass spectrometry (MS) data from different instrumental setups. The platform supports hybrid datasets from various setups such as liquid and gas chromatography (LC and GC)-MS, ion mobility spectrometry (IMS)-MS, and MS imaging. Spatial metabolomics analyses with increased annotation confidence is now feasible…
Read More Scientists Introduce “MZmine3” for Processing Big Data to Identify Hidden Chemicals in Complex Mixtures
Bioinformatics | Computational Models | Deep Learning | Drug Discovery | Machine Learning | News | Paper Summary | Trending
Predicting Drug-target Interactions using Protein Features and Wrapper Feature Selection
BySejal Saxena March 11, 2023October 22, 2026
The prediction of drug-target interactions (DTI) plays a significant role in drug development by helping in the identification of new drug targets, the repurposing of current medications for new indications, and the prediction of potential adverse drug effects. This article discusses a research study that presents a novel computational model for predicting DTIs. The model…
Read More Predicting Drug-target Interactions using Protein Features and Wrapper Feature Selection
AI | Bioinformatics | Chronic Diseases | Deep Learning | Health | News | Paper Summary | Trending
Transformers in Action: Deep Learning Aided Cardiac Patient Mortality Risk Prediction using Electronic Health Records
ByBanhita Maitra March 10, 2023March 10, 2023
Scientists from Finland have studied and explored two transformers (deep learning models), BERT and XLNet, in the context of predicting 6-month mortality in cardiac patients from over 23,000 heterogeneous electronic health records (EHR). Transformer neural networks in deep learning are methods used for sequential data modeling. Their inbuilt properties come in handy in predicting mortality…
Read More Transformers in Action: Deep Learning Aided Cardiac Patient Mortality Risk Prediction using Electronic Health Records
Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Virus
Insight into Structural Features of Hepatitis E: Princeton Researchers Discover New Path for Treatment
BySejal Saxena March 6, 2023March 6, 2023
Scientists from Princeton University have developed a comprehensive model of the structure and function of the open reading frame (ORF) 1 of Hepatitis E Virus (HEV), a type of RNA Virus that causes more than 20 million infections yearly. The ORF1 is a multifunctional protein essential for viral replication, however, it is still being determined…
Read More Insight into Structural Features of Hepatitis E: Princeton Researchers Discover New Path for Treatment
Bioinformatics | News | Paper Summary | RNA-Seq | Tools | Transcriptomics | Trending
NeuronChat Sheds Light on Neuron-Neuron Communication in the Brain through Single-cell Transcriptomics Analysis
ByBanhita Maitra March 5, 2023March 5, 2023
Scientists from the University of California, Irvine, have developed NeuronChat for inferring inter-neuronal communication using single-cell transcriptomics data. Previous cell-cell communication inference methods are based on short-range signaling enabled by diffusion or physical contact. Neurons communicate via synapses involving neurotransmitter signaling and extend over long distances. The connectome, the wiring organization of neural connectivity, is…
Read More NeuronChat Sheds Light on Neuron-Neuron Communication in the Brain through Single-cell Transcriptomics Analysis
AI | Bioinformatics | Machine Learning | News | Paper Summary | Trending
From Cell Cultures to Intelligent Systems: “Organoid Intelligence” is the New Energy-efficient Biocomputing Alternative to Artificial Intelligence
ByBanhita Maitra March 3, 2023March 3, 2023
Scientists from Johns Hopkins University lay out the possibility of energy-efficient biocomputing using brain organoids (3D brain cell cultures) that surpass in-silico computing capabilities. The recent advances in how human stem cell-derived brain organoids replicate crucial cellular, and molecular aspects of learning and memory have led to the coining of the term Organoid Intelligence (OI). The development in brain…
Read More From Cell Cultures to Intelligent Systems: “Organoid Intelligence” is the New Energy-efficient Biocomputing Alternative to Artificial Intelligence
Bioinformatics | Deep Learning | Neural Network | News | Paper Summary | Structural Biology | Trending
Improving the Accuracy of RNA-protein Complex Structure Prediction with DRPScore: A Deep Learning Algorithm
BySejal Saxena March 2, 2023March 2, 2023
Scientists have developed a new deep-learning-based approach called DRPScore for identifying native-like RNA-protein complexes essential for understanding cellular processes. DRPScore outperforms existing methods in identifying native-like structures with high accuracy, even in challenging cases involving significant conformational change. The method was tested on sets of RNA-protein complexes with varying degrees of conformational change induced by…
Read More Improving the Accuracy of RNA-protein Complex Structure Prediction with DRPScore: A Deep Learning Algorithm
Bioinformatics | Cancer Research | COVID-19 | Covid-19 News | Drug Discovery | News | Precision Medicine | RNA-Seq | Trending
Repurposing Drugs Simplified with ASGARD: A Single-cell Guided Pipeline
ByBanhita Maitra March 1, 2023October 22, 2026
Scientists from the University of Michigan have developed a single-cell guided pipeline to aid the repurposing of drugs (ASGARD) by defining a drug score for drug recommendation. The drug score is calculated by considering intercellular heterogeneity in each patient tissue sample. Single-cell RNA sequencing (scRNA-seq) is essential for addressing and analyzing intercellular heterogeneity in several…
Read More Repurposing Drugs Simplified with ASGARD: A Single-cell Guided Pipeline
Bioinformatics | Deep Learning | Machine Learning | News | Structural Biology
Designing High-Activity Luciferases with Deep Learning: A Promising Approach for Enzyme Design
ByDr. Tamanna Anwar February 28, 2023February 28, 2023
For many years, scientists have been baffled by the difficult task of designing enzymes, which is regarded as one of the most difficult challenges in biochemistry. However, the introduction of new techniques that allow the creation of scaffolds tailored to specific functions has provided new hope. The research published in Nature reports the production of highly active and…
Read More Designing High-Activity Luciferases with Deep Learning: A Promising Approach for Enzyme Design
Bioinformatics | COVID-19 | News | Paper Summary | Structural Biology | Tools | Trending
LongBondEliminator: A Novel Approach to Streamlining Molecular Dynamics Simulations
BySejal Saxena February 27, 2023January 4, 2024
Scientists from Michigan State University have introduced the LongBondEliminator, a tool designed to detect and correct ring penetrations in molecular simulations. Ring penetrations is a prevalent problem that leads to unrealistic physical behavior in simulations, and LongBondEliminator provides a powerful solution and has the potential to enhance the accuracy of simulations for a number of…
Read More LongBondEliminator: A Novel Approach to Streamlining Molecular Dynamics Simulations
Bioinformatics | Deep Learning | News | OMICS | Paper Summary | Sequencing | Tools | Trending
Meet DeepBIO: An Automated Deep Learning Platform for High-Throughput Functional Analysis of Biological Sequences
ByBanhita Maitra February 26, 2023February 26, 2023
Scientists from China have developed DeepBIO, an automated and interpretable deep learning platform for high-throughput biological sequence functional analysis. The first-of-its-kind platform enables researchers to develop new deep-learning architectures addressing particular biological questions. For any given biological sequence data, DeepBIO offers 42 state-of-the-art deep learning algorithms for model training, comparison, optimization, and evaluation in a…
Read More Meet DeepBIO: An Automated Deep Learning Platform for High-Throughput Functional Analysis of Biological Sequences
Algorithm | Bioinformatics | Genomics | News | OMICS | Paper Summary | Sequencing | Trending
NHGRI’s Verkko Algorithm: An Advancement in Genome Assembly with Notable Limitations
BySejal Saxena February 25, 2023February 24, 2023
Substantial progress has been made in assembling the first complete human genome sequence by the Telomere-to-Telomere consortium. However, complex repetitions in diploid genomes are still difficult to decode. Using lengthy, accurate reads and haplotype-specific markers, the Verkko pipeline is an automated method for assembling diploid genomes with high precision. The construction of pangenomes and chromosome-scale…
Read More NHGRI’s Verkko Algorithm: An Advancement in Genome Assembly with Notable Limitations
Bioinformatics | News | NGS | Paper Summary | RNA-Seq | Sequencing | Transcriptomics | Trending
Single-Cell RNA Sequencing: State-of-the-Art Technology and Future Prospects
ByBanhita Maitra February 24, 2023February 24, 2023
Single-cell RNA sequencing (scRNA-seq) has proved to be a powerful tool for deciphering the entire repertoire of transcripts in a single cell. Traditional sequencing techniques detect averaged transcript levels for cell populations. The emerging technology of scRNA-seq enables the classification of cell subpopulation and cell heterogeneity. The authors of the review focus on the recent…
Read More Single-Cell RNA Sequencing: State-of-the-Art Technology and Future Prospects
Big Data | Bioinformatics | Drug Discovery | News | OMICS | Trending
Big Data Analytics Reveals New Causal Pathways in Alzheimer’s Disease
ByDr. Tamanna Anwar February 23, 2023February 23, 2023
King’s College London scientists examined biological samples from hundreds of participants in a European study. The researchers studied the biological data at different stages, including genes, proteins, metabolites, cognitive function, clinical diagnosis, and the development of Alzheimer’s disease (AD). The researchers present new perspectives on the variations of specific proteins and metabolites associated with Alzheimer’s…
Read More Big Data Analytics Reveals New Causal Pathways in Alzheimer’s Disease
Algorithm | Bioinformatics | Genomics | GWAS | News | Paper Summary | Tools | Trending
Whole-Genome Population Genomics Made Easy with “PRAWNS”: A Comprehensive Tool for Multiple-genome Analysis
ByBanhita Maitra February 22, 2023February 22, 2023
Scientists from the University of Maryland have developed PRAWNS, a scalable and efficient tool for multi-genome analysis. With the unprecedented number of complete and nearly complete genomes being accessible, researchers interested in understanding the genomic basis of phenotypes, such as antibiotic resistance in bacteria, require computational tools capable of performing multiple genome comparisons efficiently. However,…
Read More Whole-Genome Population Genomics Made Easy with “PRAWNS”: A Comprehensive Tool for Multiple-genome Analysis
Bioinformatics | Cancer Research | Drug Discovery | Paper Summary | Trending
From healthy cell to cancerous growth: the alarming role of “poisoned” proteins in tumor formation
ByDr. Tamanna Anwar February 21, 2023October 22, 2026
Researchers from Scripps Research and Japan have discovered how a protein’s “poisoned” form can set off a chain of events promoting specific cancers’ growth. The research findings were published in Nature Communications. A potential drug that could return the protein to its original state was developed as a result of this study. The drug significantly…
Read More From healthy cell to cancerous growth: the alarming role of “poisoned” proteins in tumor formation
Bioinformatics | Genomics | Machine Learning | News | Paper Summary | Sequencing | Tools | Trending
Meet MinsePIE: A ML Tool to Predict Successful Insertion of Gene-edited DNA Sequences in the Genome of a Cell
ByBanhita Maitra February 20, 2023February 19, 2023
Scientists from the Wellcome Sanger Institute, Hinxton, UK, and the University of Tartu, Estonia, have developed a machine learning-based algorithm, MinsePIE, to predict prime editing insertion efficiencies. The authors performed a comprehensive analysis of prime editing efficiencies by designing a library of 3604 sequences of varying lengths and measuring the frequency of insertion into four…
Read More Meet MinsePIE: A ML Tool to Predict Successful Insertion of Gene-edited DNA Sequences in the Genome of a Cell
Antibiotic Resistance | Bioinformatics | Infectious Diseases | News | Precision Medicine | Sequencing | Trending | Virus
Local Creek Holds Secret to Fighting Deadly Infections: Newly Discovered Virus Kills Resistant Bacteria
ByDr. Tamanna Anwar February 18, 2023February 19, 2023
Scientists from the University of Southern Denmark have made an interesting discovery that may help in the fight against antibiotic-resistant bacteria. The research team has identified five novel virus species that were not known earlier to the scientific community. The finding may offer new treatment strategies against deadly infections as the virus species discovered can…
Read More Local Creek Holds Secret to Fighting Deadly Infections: Newly Discovered Virus Kills Resistant Bacteria
Bioinformatics | Cancer Research | Cell | News | Paper Summary | Trending
Unlocking the Mystery of Cancer Cell Movement: Logic Gates Provide Answers
ByBanhita Maitra February 17, 2023February 17, 2023
Scientists from Purdue University unravel cell migration direction under the influence of environmental cues using a ternary logic gate system. Cells detect several environmental cues and process intracellular signals to determine the direction of migration. Cell migration is involved in various physiological mechanisms as well as pathological processes. Signaling pathways and molecules involved in directed…
Read More Unlocking the Mystery of Cancer Cell Movement: Logic Gates Provide Answers
AI | Bioinformatics | Computational Models | Machine Learning | News | Paper Summary | Structural Biology | Trending
A New Era in Protein Conformational Ensemble Generation: The Role of Machine Learning
BySejal Saxena February 16, 2023February 16, 2023
The biological activity of a protein is determined not only by its static, three-dimensional structure but also by its dynamic characteristics, which form a variety of shapes. This study demonstrates that machine learning can be taught on protein simulation data to build physically realistic conformational ensembles without requiring expensive sampling. The researchers trained a generative…
Read More A New Era in Protein Conformational Ensemble Generation: The Role of Machine Learning
AI | Bioinformatics | Neural Network | News | Paper Summary | RNA-Seq | Transcriptomics | Trending
Meet m6Anet: A Multiple Instance Learning based Neural Network Model for Predicting RNA Modifications
ByBanhita Maitra February 15, 2023February 15, 2023
Scientists from the Genome Institute of Singapore and A*STAR Singapore have developed a neural network-based method that implements a multi-instance learning framework, “m6Anet,” to accurately detect the RNA modification m6A from genomic data. Around 150 types of RNA modifications are currently known, of which m6A methylation is noteworthy for its role in diseases. These modifications…
Read More Meet m6Anet: A Multiple Instance Learning based Neural Network Model for Predicting RNA Modifications
AI | Bioinformatics | Disease Diagnosis | Health | Machine Learning | News | Trending
From Data to Diagnosis: Leveraging EHR Data to Identify Autism within 30 Days using Machine Learning
ByDr. Tamanna Anwar February 14, 2023February 14, 2023
Autism Spectrum Disorder (ASD), also known as autism, is a global health issue affecting millions of children worldwide. According to the World Health Organization (WHO), approximately 1 in 100 children has autism globally, with the prevalence varying across different regions and countries. Identifying autism in early childhood is crucial for providing autistic children and their…
Read More From Data to Diagnosis: Leveraging EHR Data to Identify Autism within 30 Days using Machine Learning
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology
AlphaFold Teams up with Other AI Tools to Accelerate the Drug Discovery Process
BySejal Saxena February 13, 2023October 22, 2026
Structure-based drug discovery (SBDD) is a standard method for identifying prospective medications for a target by leveraging its structural information. AlphaFold, a technique for predicting protein structure, has been regarded as a helpful resource for the discovery of therapeutics for new targets with low or no structural knowledge. In this study, the scientists utilized AlphaFold…
Read More AlphaFold Teams up with Other AI Tools to Accelerate the Drug Discovery Process
Bioinformatics | Biotech | News | NGS | Paper Summary | RNA-Seq | Trending
Scientists Unlock the Mystery of Unique Fingerprint Pattern Formation
ByBanhita Maitra February 12, 2023February 12, 2023
Scientists from Edinburgh have solved the mystery behind the formation and variation in fingerprint patterns. Fingerprints are complex patterns, unique to every individual, and are determined before birth. The researchers from the University of Edinburgh unravel the molecular and cellular mechanisms underlying fingerprint ridge formation and their intricate arrangements. Fingerprint ridges are found to be…
Read More Scientists Unlock the Mystery of Unique Fingerprint Pattern Formation
Bioinformatics | Drug Discovery | Infectious Diseases | News | Proteomics | Structural Biology | Trending
The Fight Against Tuberculosis Takes a Major Step Forward: Scientists Find Flaws in Bacterium by Studying Ferredoxins
ByDr. Tamanna Anwar February 11, 2023October 22, 2026
Researchers from Skoltech, MIPT, the National Academy of Sciences of Belarus’ Institute of Bioorganic Chemistry (IBOCH NAS), and the Russian Academy of Sciences’ Institute of Biomedical Chemistry have studied the structures of ferredoxins from Mycobacterium tuberculosis and their complexes with interacting proteins. The study aims to discover new targets for anti-tuberculosis drug development by closely examining the…
Read More The Fight Against Tuberculosis Takes a Major Step Forward: Scientists Find Flaws in Bacterium by Studying Ferredoxins
Bioinformatics | Genomics | News | Paper Summary | RNA-Seq | Trending
Scientists Created a Pan-3D Genome of Soybean to Decipher Structural and Functional Differentiation
ByBanhita Maitra February 10, 2023February 10, 2023
Scientists from China have recently performed pan-3D genome analysis for soybean genomes to investigate the interplay among 3D genomic variations, structural variations (SV) as well as gene expression. Researchers applied Hi-C techniques to 27 soybean genome accessions to provide a pan-3D genome landscape of soybean and shed light on the evolutionary dynamics of 3D genomes…
Read More Scientists Created a Pan-3D Genome of Soybean to Decipher Structural and Functional Differentiation
AI | Algorithm | Bioinformatics | Deep Learning | Disease Diagnosis | Health | News | Trending
Speech Analysis Meets Artificial Intelligence: The Promise of Deep Learning for Depression Detection
ByDr. Tamanna Anwar February 9, 2023February 9, 2023
Scientists at Jinhua Advanced Research Institute and Harbin University of Science and Technology have developed a deep-learning algorithm that can identify depression through speech. This algorithm was trained to recognize emotions in spoken language by looking at various pertinent traits. Millions of people all over the world go through depression, which is a common mental…
Read More Speech Analysis Meets Artificial Intelligence: The Promise of Deep Learning for Depression Detection
Bioinformatics | News | Paper Summary | Proteomics | Trending
Generative Models for Peptide Design: Discovering Calcineurin Protein-protein Interactions Disruptors
BySejal Saxena February 9, 2023October 22, 2026
All organisms depend on protein-protein interactions (PPIs) for cellular and biological activities. This paper introduces a novel method for building peptide binders for “undruggable” protein-protein interactions. A machine learning approach generates different candidate peptides from natural binding regions from protein partners. Molecular docking and in-vitro microchip-based binding assays filter the peptides. The research confirms and…
Read More Generative Models for Peptide Design: Discovering Calcineurin Protein-protein Interactions Disruptors
Antibiotic Resistance | Infectious Diseases | News | Paper Summary | Structural Biology | Trending
Discovering the Origin of Antibiotic Resistance through DNA Replication Protein Structure Analysis
ByBanhita Maitra February 8, 2023February 8, 2023
Scientists from Barcelona have discovered a new hexameric protein structure for the RepB protein, which is involved in catalyzing replication initiation in Streptococcal plasmid pMV158, conferring antibiotic resistance to tetracycline. The new hexameric structure, obtained using biochemical methods and X-ray crystallography, is found to render flexibility, which attributes to the dual functionality of the protein,…
Read More Discovering the Origin of Antibiotic Resistance through DNA Replication Protein Structure Analysis
AI | Bioinformatics | Deep Learning | Disease Diagnosis | Health | News | Trending
The Future of Rare Disease Prediction: Machine Learning Takes the Lead
ByDr. Tamanna Anwar February 7, 2023February 7, 2023
The POPDx model does not require extensive patient datasets, which makes it potentially useful for patients with rare diseases. The POPDx framework was created to effectively identify a wide variety of phenotypes among participants in the UK Biobank study. To provide a thorough analysis, it makes use of a wide variety of patient data, including…
Read More The Future of Rare Disease Prediction: Machine Learning Takes the Lead
Bioinformatics | Database | Drug Discovery | GWAS | News | NGS | Paper Summary | Precision Medicine | Sequencing | Trending
AGORA2: The Key to Personalized Medicine through Genome-wide Metabolic Reconstruction of Human Microbes
BySejal Saxena February 6, 2023February 6, 2023
The digestive system is home to trillions of bacteria, which are very different in each person based on their gender, age, race, lifestyle, and health. For precision medicine to include microbial metabolism, computer models would have to be expandable and able to resolve strains and molecules. This study introduces us to AGORA2 – assembly of…
Read More AGORA2: The Key to Personalized Medicine through Genome-wide Metabolic Reconstruction of Human Microbes
Bioinformatics | News | OMICS | Paper Summary | Proteomics | Trending
In-depth Mapping of Protein Localizations in Whole Tissue Using Micro-scaffold Assisted Spatial Proteomics (MASP)
ByBanhita Maitra February 5, 2023February 5, 2023
Researchers from the Jun Qu lab at SUNY Buffalo, New York, have developed a revolutionary method for in-depth mapping of protein localization in whole tissue. The method implements the cutting-edge technique of micro-scaffold-assisted spatial proteomics (MASP). The daunting task of accurate, in-depth mapping of protein localizations at the whole-tissue level has been achieved by using…
Read More In-depth Mapping of Protein Localizations in Whole Tissue Using Micro-scaffold Assisted Spatial Proteomics (MASP)
Bioinformatics | Cancer Research | Drug Discovery | News | NGS | OMICS | Proteomics
New Hope in the Fight Against Cancer: Scientists Discover Nutrient that Cancer Cells Crave
ByDr. Tamanna Anwar February 4, 2023October 22, 2026
Cancer is one of the prominent causes of death globally, and discovering new methods to prevent and cure it is important for public health. Understanding the particular nutrients that cancer cells require is one of the strategies researchers are investigating to fight the disease. Arginine is one of the important amino acids produced by our…
Read More New Hope in the Fight Against Cancer: Scientists Discover Nutrient that Cancer Cells Crave
AI | Algorithm | Bioinformatics | Database | News | Paper Summary | Structural Biology | Tools | Trending
Meet AlphaFill: An AI Algorithm to Fill Missing Ligands and Cofactors in AlphaFold Models
BySejal Saxena February 2, 2023February 2, 2023
According to Levinthal’s paradox, each protein may adopt around 10300 distinct structures. We now know 3-D structures for about 98% of the human proteome thanks to DeepMind’s AI system, AlphaFold. However, AlphaFold has limitations, such as its inability to generate coordinates for tiny molecules and ligands that are critical to the protein’s activity. Researchers from…
Read More Meet AlphaFill: An AI Algorithm to Fill Missing Ligands and Cofactors in AlphaFold Models
Bioinformatics | COVID-19 | Deep Learning | Drug Discovery | Neural Network | News | Paper Summary | Tools | Trending
DGNN-DDI: A Cutting-edge Tool for Drug-Drug Interaction Prediction using Dual Graph Neural Network
ByBanhita Maitra February 1, 2023February 1, 2023
Scientists from Shaanxi Normal University, China, developed a novel Drug-Drug-Interactions (DDI) prediction tool that implements a dual graph neural network architecture to incorporate chemical substructure information as well as substructure interaction information of drugs. This never-before-implemented approach has the potential to identify synergistic drug combinations for COVID-19. Why do we need to predict DDI? Drug-Drug…
Read More DGNN-DDI: A Cutting-edge Tool for Drug-Drug Interaction Prediction using Dual Graph Neural Network
Bioinformatics | COVID-19 | Covid-19 News | Drug Discovery | Gene Expression | News | NGS | Paper Summary | RNA-Seq | SARS-CoV-2 | Trending
New Study Finds Connection Between Immune Response & Persistent Smell Loss Post-COVID-19
BySejal Saxena January 31, 2023January 31, 2023
Most SARS-CoV-2 patients experience anosmia, or a loss of smell, which can linger for months after recovery. According to olfactory epithelium samples taken from 24 biopsies, T cell-mediated inflammation continues in the olfactory epithelium even after SARS-CoV-2 has been removed from the tissue, indicating a mechanism for long-term post-COVID-19 smell loss. The severe acute respiratory…
Read More New Study Finds Connection Between Immune Response & Persistent Smell Loss Post-COVID-19
AI | Bioinformatics | Computational Models | Deep Learning | Drug Discovery | Genetic Engineering | News | Paper Summary | Tools | Transcriptomics | Trending
Meet ZFDesign: A Universal Deep Learning Model for Zinc Finger Design Enabling Transcription Factor Reprogramming
ByBanhita Maitra January 30, 2023January 30, 2023
Controlling gene expression by engineering Cys2His2 zinc finger (ZF) domains to bind particular target sequences in the genome has many therapeutic applications. However, due to their intricate structure, designing these domains to interact with DNA is challenging. To address the problem, scientists from the University of Toronto and New York University have developed a deep…
Read More Meet ZFDesign: A Universal Deep Learning Model for Zinc Finger Design Enabling Transcription Factor Reprogramming
Bioinformatics | Cancer Research | Machine Learning | News | Paper Summary | Precision Medicine | Trending
Machine Learning in Oncology: A Tabular Machine Learning Approach to Pan-cancer Tumor-only Variant Calling
BySejal Saxena January 29, 2023January 16, 2024
Accurately identifying somatic mutations and differentiating them from germline variations is critical for precision oncology and precise tumor-mutational burden (TMB) computation. For this purpose, three trained machine-learning models, TabNet, XGBoost, and LightGBM, were utilized, and state-of-the-art performance was achieved, with concordance between matched-normal and tumor-only TMB improving from R2=0.006 to R2=0.73. The racial biases in…
Read More Machine Learning in Oncology: A Tabular Machine Learning Approach to Pan-cancer Tumor-only Variant Calling
AI | Bioinformatics | Biomedical Engineering | Computational Models | Deep Learning | Drug Discovery | Machine Learning | News | Proteomics | Trending
AI Proteins: Unlocking the Potential of Protein Generation from Scratch with Natural Language Model “ProGen”
ByDr. Tamanna Anwar January 28, 2023October 22, 2026
Scientists from the University of California, San Francisco, have created an inventive AI system that can create entirely new enzymes from scratch. Even though the amino acid sequences of these synthetic enzymes differ significantly from those of any naturally occurring protein, they have demonstrated remarkable efficacy in laboratory experiments. In other words, using state-of-the-art technology,…
Read More AI Proteins: Unlocking the Potential of Protein Generation from Scratch with Natural Language Model “ProGen”
Bioinformatics | Database | News | OMICS | Paper Summary | Tools | Trending
Luminary for Lipidomics Research Applications: Guiding the Choice of Informatics Software and Tools
ByBanhita Maitra January 27, 2023January 27, 2023
There has been an increase in research in numerous areas of biology and medicine due to the development of mass spectrometry lipidomics. As a result, massive amounts of raw data have been produced, which calls for cutting-edge techniques to handle automated data processing. Several software tools that meet particular needs have been developed to address…
Read More Luminary for Lipidomics Research Applications: Guiding the Choice of Informatics Software and Tools
Bioinformatics | Deep Learning | Drug Discovery | News | Paper Summary | Structural Biology | Trending
De Novo Drug Design Using Generative Deep Learning: Implementing Chemical Language Models with Molecular Structures and Bioactivity
BySejal Saxena January 26, 2023January 26, 2023
Chemical language models (CLMs) can be used to construct molecules with desired features. Textual representations of novel chemical structures, such as simplified molecular input line entry system (SMILES) strings, are generated using CLMs. The ability of generative models to learn a training distribution of molecules determines their usefulness for designing new functional substances. Through the…
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