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

AI | Bioinformatics | Biomedical Engineering | Cancer Research | Machine Learning | News | Paper Summary | Trending
Federated Machine Learning Powers the Biggest Brain Tumor Study to Date while Protecting Patient’s Data
ByCatherene Tomy December 8, 2022December 8, 2022
Federated machine learning enables the largest brain tumor study ever conducted without sharing patient data by allowing researchers to securely analyze distributed datasets while maintaining data privacy. The breakthrough research from Penn Medicine and Intel Corporation published in Nature Communications has the potential to revolutionize medical research and improve our understanding of brain tumors. It also provides…
Read More Federated Machine Learning Powers the Biggest Brain Tumor Study to Date while Protecting Patient’s Data
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
AI | Bioinformatics | Computational Models | Machine Learning | News | Paper Summary
Scientists Develop a Machine Learning Model ‘DxFormer’ for Automated Disease Diagnosis
ByShwetha S December 2, 2022December 2, 2022
Fudan University researchers introduced DxFormer, a new automatic diagnostic framework in which each symptom is regarded as a token, formalizing symptom inquiry and disease diagnosis to a language generation model and a sequence classification model, respectively. The decoder encoder structure, an inverted version of Transformer, was utilized to learn the representation of symptoms by jointly…
Read More Scientists Develop a Machine Learning Model ‘DxFormer’ for Automated Disease Diagnosis
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 | Deep Learning | GWAS | News
A Novel Deep Learning Framework Identifies Gene-Gene Interactions for a Given Phenotype
ByShwetha S November 15, 2022November 15, 2022
A deep learning framework has been developed by researchers under the direction of Tianyu Cui, a Ph.D. student in the Department of Computer Science at Aalto University, to identify the gene-gene interactions underlying a given phenotype by taking into account all single nucleotide polymorphisms within a set of genes or complex interactions and calculating their…
Read More A Novel Deep Learning Framework Identifies Gene-Gene Interactions for a Given Phenotype
Bioinformatics | Covid-19 News | News | NGS | Paper Summary | RNA-Seq | SARS-CoV-2 | Structural Biology
Researchers Elucidated the Dynamic RNA Structurome and its Potential in Targeted Therapeutics
ByMahi Sharma November 14, 2022November 29, 2022
With a thorough potential of the Ribonucleic Acids (RNA) in cellular processes, the molecule is deemed more than just being transitionary and has emerged as a master regulator of cellular processes. The regulatory functions to code proteins and untranslated regions in mRNA significantly contribute towards post-translational modifications. A review published in Nature Reviews Genetics gives biological insights…
Read More Researchers Elucidated the Dynamic RNA Structurome and its Potential in Targeted Therapeutics
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
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

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SQUID: A New Generative Model for Shape-Conditioned Generation of 3D Molecules for Structure-Based Drug Design

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