Bioinformatics

Bioinformatics | Drug Discovery | News | Paper Summary
SQUID: A New Generative Model for Shape-Conditioned Generation of 3D Molecules for Structure-Based Drug Design
ByMahi Sharma October 19, 2022January 27, 2024
Researchers from MIT University, Cambridge, have introduced a novel generative model, ‘SQUID’, to facilitate the shape-conditioned generation of chemically diverse molecules for drug design in 3D conformation. The team has successfully introduced equivariant deep working models to challenge current 2D generative models. Introduction Computer-aided drug design, CADD, has been reformed by integrating generative models. CADD…
Read More SQUID: A New Generative Model for Shape-Conditioned Generation of 3D Molecules for Structure-Based Drug Design
Bioinformatics | Cancer Research | COVID-19 | GWAS | Health | News | NGS | Paper Summary | RNA-Seq | Transcriptomics | Trending
Single-cell RNA Sequencing and GWAS Data Integration Discover New Disease Cell Types and Pathways
ByShwetha S October 18, 2022October 18, 2022
A brand-new framework called sc-linker has been proposed by researchers from the Broad Institute of MIT and Harvard that connects human illness and phenotypes to different cell types and physiological processes. This is done by integrating Genome-Wide Association Studies summary statistics, epigenomic data, and single-cell RNA (scRNAseq) sequence data from multiple tissues, cells, diseases, and…
Read More Single-cell RNA Sequencing and GWAS Data Integration Discover New Disease Cell Types and Pathways
Bioinformatics | Cancer Research | Computational Models | News | Paper Summary | RNA-Seq | Transcriptomics | Trending
Attention-based Multi-view Graph Collaborative Learning Model ‘stMVC’ to Decipher Tumor Heterogeneity in Spatial Transcriptomics Data
ByMahi Sharma October 17, 2022October 16, 2022
Recent advancements in SRT (Spatial Resolved Transcriptomics) technology has allowed in-depth research to measure gene activity in tissue samples and map the activity based on their composition. A collaborative team of researchers from China has introduced a multi-view graph collaborative model, ‘stMVC’ (Spatial Transcriptomics data analysis by Multiple View Collaborative-learning), to analyze SRT data and elucidate tissue heterogeneity to…
Read More Attention-based Multi-view Graph Collaborative Learning Model ‘stMVC’ to Decipher Tumor Heterogeneity in Spatial Transcriptomics Data
Bioinformatics | News | Paper Summary | Structural Biology | Trending
Demystifying Large Protein Complex Structures Using AlphaFold and Monte Carlo Tree Search
ByShwetha S October 16, 2022October 16, 2022
Researchers from Stockholm University, Sweden, have developed a novel bioinformatics pipeline to predict the structure of large protein molecules, such as the nuclear pore or the 26S proteasome complex, using AlphaFold and Monte Carlo Tree Search. A protein complex is a group of two or more polypeptide chains associated together. These biological entities play a…
Read More Demystifying Large Protein Complex Structures Using AlphaFold and Monte Carlo Tree Search
Bioinformatics | Drug Discovery | Health | News | Paper Summary | Trending
DrugRep: An Automated and Parameter-Free Virtual Screening Tool for Drug Repurposing
ByMahi Sharma October 15, 2022October 22, 2026
Drug repurposing has been strategically used to modulate the usage of pre-existing drugs. The virtual screening tool DrugRep facilitates computational screening using both receptor and ligand-based methods. Being freely available, it provides the unstinted potential for repurposing and investing in current pharmacology. Historically, introducing novel drugs bears challenges in terms of exploring and introducing them…
Read More DrugRep: An Automated and Parameter-Free Virtual Screening Tool for Drug Repurposing
Big Data | Bioinformatics | Health | Machine Learning | News | Paper Summary | Trending
Insurance Claim Data and Machine Learning Aids in the Early Detection of Autism Spectrum Disorder
ByShwetha S October 14, 2022October 14, 2022
Researchers from Pennsylvania State University have put forth a novel machine-learning approach to help predict Autism Spectrum Disorder in children at a very young age, between 18 to 30 months. Such early detection can vastly help both the patients and the clinicians to improve treatment outcomes. The authors define Autism Spectrum Disorder (ASD) as a…
Read More Insurance Claim Data and Machine Learning Aids in the Early Detection of Autism Spectrum Disorder
Bioinformatics | Covid-19 News | Drug Discovery | News | Paper Summary | SARS-CoV-2 | Trending | Virus
A Systematic Proteome-scale Contactome Map Reveals How SARS-CoV-2 Communicates with Human Cells
ByMahi Sharma October 13, 2022October 22, 2026
Witnessing the most wrecking pandemic in a decade, COVID-19 visibly tested the potential of healthcare advancements. A collaborative team of researchers addressed earlier loopholes in research by systematically identifying protein interaction contacts between humans and the sars-cov-2 proteome. The team successfully evaluated the ‘contactome theory’, associating the host genome with morbidity and the COVID-19 community…
Read More A Systematic Proteome-scale Contactome Map Reveals How SARS-CoV-2 Communicates with Human Cells
Bioinformatics | Machine Learning | Neural Network | News | Paper Summary | Trending
KAGE – A Fast Alignment-free Graph-based Genotyper for SNPs and Short Indels
ByShwetha S October 12, 2022October 12, 2022
Researchers from the University of Oslo have developed a novel genotyper named KAGE for detecting SNPs, short insertions, and deletions. KAGE uses an alignment-free word-based approach to genotype variants in a shorter duration, higher accuracy, and less memory. Genotyping refers to the process of detecting the genotype (genetic makeup) of an individual using biological techniques…
Read More KAGE – A Fast Alignment-free Graph-based Genotyper for SNPs and Short Indels
AI | Bioinformatics | Deep Learning | News | Paper Summary
Predicting Genome-Wide Chromatin Loop using Deep Learning Model ‘DLoopCaller’
ByCBIRT October 11, 2022October 11, 2022
Throughout the years, dissecting gene regulation has been a major challenge for researchers. Using high-throughput sequencing, understanding chromatin landscapes and conformations has set a new era in genomic medicine. Researchers from Shanghai, China, have presented DLoopCaller – a deep learning approach to predict chromatin architecture to identify gene regulation down to transcription factor. Chromatin is…
Read More Predicting Genome-Wide Chromatin Loop using Deep Learning Model ‘DLoopCaller’
Bioinformatics | Cancer Research | Computational Models | Health | Machine Learning | News | Paper Summary | Trending
A Novel Semi-Supervised Machine Learning Model for Patch-based Breast Cancer Classification
ByShwetha S October 10, 2022October 9, 2022
Researchers from Tartu University have put forth a semi-supervised machine learning framework to detect invasive ductal carcinoma using a small amount of labeled breast cancer histological data. Breast cancer is one of the most common cancers. According to the world health organization (WHO), nearly 2.3 million women worldwide have been affected with breast cancer, with…
Read More A Novel Semi-Supervised Machine Learning Model for Patch-based Breast Cancer Classification
AI | Bioinformatics | Deep Learning | News | Paper Summary | Trending
Explainable AI – Deep Learning Models: Black Box to Emerging Genomics Research
ByMahi Sharma October 9, 2022October 9, 2022
Deep learning extensively affects studying genetics and the breakthrough research associated with them. The study focuses on understanding the building of complex models rather than complex datasets using model interpretations in Explainable Artificial Intelligence (xAI). This helps in understanding the utility of complex models to decipher biological datasets. Artificial intelligence-based deep learning models are known…
Read More Explainable AI – Deep Learning Models: Black Box to Emerging Genomics Research
Bioinformatics | Genomics | GWAS | News | Paper Summary | Trending
A New Study Reveals the Landscape and Evolution of Nuclear-Mitochondrial Segments
ByShwetha S October 8, 2022October 8, 2022
Researchers from Cambridge University have reported the presence of nuclear-mitochondrial segments (NUMT) in a sample population of 66,083 people with 12,509 cancer samples. Whole genome sequencing (WGS) of the samples observed de novo NUMT of one in every 10^4 births and one in every 10^3 cancers, indicating that DNA translocation is a continuing process. Endosymbiosis…
Read More A New Study Reveals the Landscape and Evolution of Nuclear-Mitochondrial Segments
Big Data | Bioinformatics | Drug Discovery | Machine Learning | Neural Network | News | Paper Summary | RNA-Seq | Trending
HAL-X: A Novel Clustering Algorithm for Rapid Single-Cell Data Analysis for Drug Discovery
ByMahi Sharma October 7, 2022October 22, 2026
The novel clustering algorithm HAL-x provides insights into single-cell clustering, bridging the biomedicine sciences for healthcare purposes. With its specificity and sensitivity, it allows the generation of multiple-clustering for in-depth analysis of high-dimensional data. The future directions of algorithms are extremely promising in understanding disease, disease progression, and drug discovery. Throughout the years, clustering has…
Read More HAL-X: A Novel Clustering Algorithm for Rapid Single-Cell Data Analysis for Drug Discovery
AI | Bioinformatics | Chronic Diseases | Health | Machine Learning | News | Trending
Unraveling Diseases with Data – Machine Learning Helps Identify New Nonlinear Progression Patterns in Neurodegenerative Disorders
ByShwetha S October 6, 2022November 24, 2023
Researchers from the MIT-IBM Watson AI lab have developed a new machine learning-based model that recognizes ALS disease progression. The research will help design future clinical trials and discover mechanisms behind the disease. The study also highlights that the model can be extrapolated to other neurodegenerative disorders, like Alzheimer’s and Parkinson’s, to trace disease patterns. Neurodegenerative diseases…
Read More Unraveling Diseases with Data – Machine Learning Helps Identify New Nonlinear Progression Patterns in Neurodegenerative Disorders
AMR Alert | Antibiotic Resistance | Bioinformatics | Health | Infectious Diseases | Metagenomics | News | Paper Summary | Trending
Understanding the Population Dynamics for AMR Burden due to Carbapenemase-producing Enterobacteriaceae in Gut Microbiome
ByMahi Sharma October 5, 2022January 8, 2024
Scientists from A*STAR’s Genome Institute of Singapore (GIS) discovered that carbapenemase-producing Enterobacteriaceae (CPE) could hide out among gut bacteria in asymptomatic humans. Long-term research to understand microbiome ecology within the population suggests visible shifts in microbial pathways assisting in the colonization of Enterobacteriaceae favoring CPE (Carbapenemase-producing Enterobacteriaceae ) infections. The study provides imperative insight into…
Read More Understanding the Population Dynamics for AMR Burden due to Carbapenemase-producing Enterobacteriaceae in Gut Microbiome
Bioinformatics | Deep Learning | Machine Learning | News | Paper Summary | Tools | Trending
Researchers Identified Deep Learning Tools as the Top Performers for Predicting Long Non-coding RNA
BySrishti Sharma October 3, 2022October 3, 2022
New RNA transcripts have been discovered as a result of the growing amount of transcriptomic data. Bioinformatic tool developers have had difficulty separating long non-coding RNA (lncRNA) from protein-coding messenger RNA (mRNA). Currently, tools implementing deep learning architectures have been developed to accomplish this task, but their potential to discover sequence features and their interactions…
Read More Researchers Identified Deep Learning Tools as the Top Performers for Predicting Long Non-coding RNA
Bioinformatics | Data Science | News | NGS | OMICS | Paper Summary | RNA-Seq | Sequencing | Trending
In a Benchmark Study, Scientists Investigated the Integration of Temporal Sequencing Modalities for Trajectory Inference and Disease Prediction
ByMahi Sharma October 2, 2022October 1, 2022
Recent advancements in trajectory inferences have unfolded a new side of bioinformatics, i.e., single-cell analysis. The research group from the University of Northern Carolina School of Medicine benchmark study addressed gaps in capturing temporal changes in a single-cell state. Interpretation of dynamic phenotypes using ten datasets spanning different biological environments at three distinct temporal stages….
Read More In a Benchmark Study, Scientists Investigated the Integration of Temporal Sequencing Modalities for Trajectory Inference and Disease Prediction
AI | Bioinformatics | Cancer Research | Machine Learning | News | Paper Summary | Tools | Trending
New AI Tool ‘SigProfilerExtractor’ Identifies Mutational Signature Linked To Tobacco Smoking and Bladder Cancer
BySrishti Sharma September 30, 2022September 30, 2022
A new powerful machine learning tool, ‘SigProfilerExtractor‘ has identified a link between bladder cancer and tobacco smoking. The study was led by researchers at the University of California San Diego School of Medicine and published in the journal Cell Genomics. The study may help researchers determine what environmental factors could cause cancer in certain patients, such…
Read More New AI Tool ‘SigProfilerExtractor’ Identifies Mutational Signature Linked To Tobacco Smoking and Bladder Cancer
Bioinformatics | Cancer Research | Drug Discovery | Machine Learning | News | Paper Summary | Trending
Eliminating the Confounder Bias – A Radical Approach for Better Identification of Cancer Drug Targets
ByShwetha S September 29, 2022October 22, 2026
Researchers from Jilin University have constructed a machine learning-based model that reduces confounders’ effects to identify potential driver genes involved in cancer initiation and progression. Cancer is one of the deadliest diseases worldwide. According to the World Health Organization (WHO), cancer has claimed the lives of nearly 10 million people in 2020. Mutations in the…
Read More Eliminating the Confounder Bias – A Radical Approach for Better Identification of Cancer Drug Targets
Bioinformatics | Metagenomics | News | Paper Summary | Sequencing | Tools | Trending
iNAP: An Integrated Network Analysis Pipeline for Microbiome Studies in Complex Ecosystems
ByMahi Sharma September 28, 2022September 28, 2022
Microbial network analysis is an acceptable approach to investigating microbiome and metagenomic datasets and finding insights into a complex ecosystem. Ye Deng et al. introduced an integrated pipeline, iNAP, for network construction and visualization to help researchers understand microbial ecology without prior knowledge of bioinformatics or statistical programming skills. Understanding and deducing information from microbial…
Read More iNAP: An Integrated Network Analysis Pipeline for Microbiome Studies in Complex Ecosystems
AMR Alert | Bioinformatics | Infectious Diseases | Machine Learning | Metagenomics | News | NGS | Paper Summary | Trending
Scientists Investigated Microbial Communities and Resistomes in Relation to Interconnected Humans, Soil, and Livestock
BySrishti Sharma September 27, 2022September 27, 2022
Antimicrobial resistance (AMR) may be reservoired in intensive livestock farms, posing a threat to surrounding communities. The gut microbiome of livestock, workers, and their households, as well as microbial communities in carcasses and soil, were investigated using shotgun metagenome sequencing, machine learning (ML), and culture-based methods at a poultry farm in China. In this study,…
Read More Scientists Investigated Microbial Communities and Resistomes in Relation to Interconnected Humans, Soil, and Livestock
Bioinformatics | Cancer Research | News | NGS | Paper Summary | Sequencing | Trending
Mathematical Modeling Bridges Chromatin Architecture with Potential in Genome Medicine
ByMahi Sharma September 26, 2022September 26, 2022
Scientists from the University of Michigan employed hypergraph theory, utilizing long sequence reads to map genome-wide multi-ways to identify chromatin architecture within the human genome. Understanding how a cell is organized could help biologists develop treatments that halt cancer and other diseases. The kinetics of high-order chromatin composition is known to play a role in…
Read More Mathematical Modeling Bridges Chromatin Architecture with Potential in Genome Medicine
AI | Bioinformatics | COVID-19 | Drug Discovery | News | Structural Biology | Tools | Trending
Accelerating the Discovery of New Drugs with AI-based Screening Methods
ByDr. Tamanna Anwar September 25, 2022September 29, 2022
The researchers from the University of Central Florida identified promising drug candidates using an AI-based tool, “AttentionSiteDTI,” that uses natural language to model drug-target protein interactions. Drug discovery has become a major bottleneck in modern medicine. Researchers have developed several methods to speed up the process in recent years, such as high-throughput screening (HTS). HTS…
Read More Accelerating the Discovery of New Drugs with AI-based Screening Methods
AI | Bioinformatics | Deep Learning | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Trending
Meet “ProteinMPNN,” A Robust Deep Learning-based Protein Sequence Design Algorithm
BySrishti Sharma September 24, 2022October 22, 2026
Predicting protein structure has been revolutionized by machine learning over the past two years. A similar breakthrough in protein design has now been reported in the journal Science. The researchers from the Baker lab at the University of Washington demonstrate that machine learning makes the design of proteins much more accurate and faster with a…
Read More Meet “ProteinMPNN,” A Robust Deep Learning-based Protein Sequence Design Algorithm
Bioinformatics | Metagenomics | News | NGS | Paper Summary | Sequencing | Trending
Microbiome Data Analysis using Differential Abundance Methods – A Benchmark Study
BySrishti Sharma September 22, 2022September 22, 2022
In order to perform an extensive benchmarking of the known tools for differential abundance analysis, the researchers from the University of Padova used a simulator of microbiome data to create a simulation framework based on microbiome data. This is the first step towards the development of a robust, reliable, and fair simulation framework that will…
Read More Microbiome Data Analysis using Differential Abundance Methods – A Benchmark Study
AI | Bioinformatics | Health | News | Trending
CheXzero: A Tool to Identify Pathologies from Unannotated Chest X-ray Images Using Self-supervised Learning
ByDr. Tamanna Anwar September 21, 2022January 26, 2023
The new tool “CheXzero” improves clinical AI design by overcoming the major hurdle of labeling datasets for model training. Scientists at Harvard Medical School and Stanford University have developed an artificial intelligence diagnostic tool that can detect diseases directly from natural language descriptions of chest X-rays. This is a major step forward in clinical AI…
Read More CheXzero: A Tool to Identify Pathologies from Unannotated Chest X-ray Images Using Self-supervised Learning
Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Tools | Trending
DeepFold: A Fast and Accurate Method for Ab Initio Protein Structure Prediction using Deep Learning Potentials
BySrishti Sharma September 20, 2022January 26, 2023
Scientists from the University of Michigan developed an open-source program, DeepFold, to quickly construct accurate protein structure models from deep learning-based potentials. In spite of recent progress in protein structure prediction, it is still necessary to improve the accuracy of models for proteins lacking sequence and/or structure homologs. The DeepFold program uses multi-task deep residual…
Read More DeepFold: A Fast and Accurate Method for Ab Initio Protein Structure Prediction using Deep Learning Potentials
Bioinformatics | News | Structural Biology | Trending
Vanderbilt University Researchers Suggest a New Mechanism for the Lipid Transporter
ByDr. Tamanna Anwar September 19, 2022September 18, 2022
New research from Vanderbilt University suggests that a protein involved in the production of high-density lipoprotein (HDL) works differently than previously believed. High-density lipoproteins (HDL) are a type of protein that helps transport cholesterol throughout the body. HDL particles have a higher concentration of cholesterol than low-density lipoproteins. The HDL cholesterol or “good cholesterol” carries…
Read More Vanderbilt University Researchers Suggest a New Mechanism for the Lipid Transporter
AI | Bioinformatics | Infectious Diseases | News | Precision Medicine | Trending
Researchers at Tufts use Artificial Intelligence to Improve Tuberculosis Treatments
ByDr. Tamanna Anwar September 17, 2022September 16, 2022
A challenge to tuberculosis treatment regimen design is the need to combine three or more antibiotics. The study shows how machine learning can provide a data-driven perspective on this challenge, so researchers can consider new drug combinations to provide better treatments. The researchers believe this new approach will increase scientists’ ability to determine which drug…
Read More Researchers at Tufts use Artificial Intelligence to Improve Tuberculosis Treatments
Big Data | Bioinformatics | Computational Models | News
MIT Biologists Develop a New Computational Approach to Gain Insights into Repetitive Protein Sequences
ByDr. Tamanna Anwar September 16, 2022September 16, 2022
The computational analysis of proteins reveals that many repetitive sequences are shared across proteins and show similarities in species from bacteria to humans. MIT biologists have found a new method to study proteins that have similar sequences as a unified group. The researchers used dot plots and dimensionality reduction to identify “low-complexity regions” (LCR)/copy relationships…
Read More MIT Biologists Develop a New Computational Approach to Gain Insights into Repetitive Protein Sequences
AI | Big Data | Bioinformatics | Drug Discovery | News | Trending
Microsoft and Novo Nordisk Collaborate to Accelerate Drug Discovery and Development using Big Data and Artificial Intelligence
ByDr. Tamanna Anwar September 15, 2022October 22, 2026
Novo Nordisk, a leading global healthcare company headquartered in Denmark, has entered into a new strategic collaboration with Microsoft Corp. to accelerate drug discovery and development using big data and artificial intelligence. A new strategic collaboration between the two companies aims to combine Microsoft’s capabilities in data science, cloud computing, and artificial intelligence (AI) with…
Read More Microsoft and Novo Nordisk Collaborate to Accelerate Drug Discovery and Development using Big Data and Artificial Intelligence
AI | Bioinformatics | Machine Learning | News | Precision Medicine | Trending
Scientists Develop an Artificial Intelligence Tool that Could Reduce the Side Effects of Common Drugs
ByDr. Tamanna Anwar September 14, 2022September 14, 2022
It may be possible for clinicians to use artificial intelligence to identify patients who are most prone to experiencing harmful side effects when taking some common antidepressants, antihistamines, and bladder medications. In a study published in Age and Ageing, researchers from the Universities of Exeter and Kent and Medway NHS and Social Care Partnership Trust…
Read More Scientists Develop an Artificial Intelligence Tool that Could Reduce the Side Effects of Common Drugs
AI | Bioinformatics | Cancer Research | Deep Learning | Health | News | Precision Medicine | Tools | Trending
Scientists Develop an Improved Method for Detecting Myeloma Bone Disease using Deep Learning Coupled Photon-counting CT
ByDr. Tamanna Anwar September 13, 2022September 13, 2022
Scientists have developed a new CT technique using artificial intelligence (AI) to spot multiple myeloma-related bone diseases, using lower radiation doses than conventional CT, according to a study published in Radiology, a journal of the Radiological Society of North America. After nearly two decades of development, the technology was used in clinical practice in 2021….
Read More Scientists Develop an Improved Method for Detecting Myeloma Bone Disease using Deep Learning Coupled Photon-counting CT
AI | Bioinformatics | COVID-19 | Covid-19 News | Deep Learning | News | SARS-CoV-2 | Trending
A New AI Model can Detect COVID-19 Cases by Analyzing Changes in Voice Data
ByDr. Tamanna Anwar September 12, 2022September 12, 2022
A deep learning model based on voice data from crowd-sourced audio samples detects COVID-19 cases by analyzing subtle vocal changes. At an international congress of the European Respiratory Society in Barcelona, Spain, held from 4th–6th September, researchers presented a study that uses deep learning to identify COVID-19 patients using voice data. The research findings were…
Read More A New AI Model can Detect COVID-19 Cases by Analyzing Changes in Voice Data
Antibiotic Resistance | Bioinformatics | COVID-19 | Covid-19 News | Drug Discovery | News | SARS-CoV-2 | Trending | Virus
Researchers at Mount Sinai Determined the Crystal Structure of the SARS-CoV-2 Key Enzyme, Paving the Way for Novel Antivirals
ByDr. Tamanna Anwar September 11, 2022October 22, 2026
Researchers at Mount Sinai have solved the high-resolution crystal structure of a critical enzyme of SARS-CoV-2, leading to the development of new antivirals. This is a major breakthrough in the battle against SARS-CoV-2 and could lead to the development of new and more effective antiviral drugs. SARS-CoV-2 is a deadly virus that has killed millions…
Read More Researchers at Mount Sinai Determined the Crystal Structure of the SARS-CoV-2 Key Enzyme, Paving the Way for Novel Antivirals
Bioinformatics | Cancer Research | News | NGS | OMICS | Paper Summary | RNA-Seq | Tools | Trending
Cancer Omics Data Analysis Simplified with a Graphical Interface-driven Bioinformatics Pipeline ‘iCOMIC’
BySrishti Sharma September 10, 2022January 3, 2024
Researchers from the Indian Institute of Technology, Madras, present iCOMIC, a tool for quickly analyzing genomic data. With iCOMIC, users can analyze whole genome and exome sequencing data as well as RNA-Seq data using several pre-configured workflows. Developed as an open-source, standalone tool characterized by a Python-based GUI and automated bioinformatics pipelines for DNA-Seq and…
Read More Cancer Omics Data Analysis Simplified with a Graphical Interface-driven Bioinformatics Pipeline ‘iCOMIC’
Bioinformatics | News | Paper Summary | RNA-Seq | Sequencing | Trending
Scientists Construct a Single-cell Level Cross-species Cell Landscape by Integrating Over 2.6 Million Single Cells
BySrishti Sharma September 9, 2022September 9, 2022
Life is based on individual cells. Landscape dynamics across species have not been compared despite extensive efforts to characterize cellular heterogeneity. A large number of cell landscapes were mapped for mice, zebrafish, and Drosophila at multiple life stages using single-cell RNA sequencing (scRNA-seq). With over 2.6 million single cells integrated, the construction of a cross-species…
Read More Scientists Construct a Single-cell Level Cross-species Cell Landscape by Integrating Over 2.6 Million Single Cells
Bioinformatics | COVID-19 | Infectious Diseases | News | Tools | Trending
MVsim – A Toolset for Simulating Complex Molecular Interactions Could Improve Cancer and COVID-19 Treatments
ByDr. Tamanna Anwar September 8, 2022September 8, 2022
MVsim is a new application suite that enables the quantification, design, and mechanistic evaluation of multivalent binding interactions. It can be used to simulate both monospecific and multispecific multivalent ligand-receptor interactions accurately, having potential applications for protein engineering, molecular and cellular analysis, as well as drug design. The University of Minnesota Twin Cities biomedical engineers have…
Read More MVsim – A Toolset for Simulating Complex Molecular Interactions Could Improve Cancer and COVID-19 Treatments
Bioinformatics | Infectious Diseases | Machine Learning | News | Trending
Machine Learning Reveals How Bacterial Population Growth is Linked to the Environment
ByDr. Tamanna Anwar September 7, 2022September 10, 2022
University of Tsukuba researchers used machine learning to discover that differentiation in decision-making factors for the lag, growth, and saturation phases of bacterial population growth safeguards the population from extinction. The large datasets produced in the study and the use of machine learning to handle complex modeling will be of interest to the biology community….
Read More Machine Learning Reveals How Bacterial Population Growth is Linked to the Environment
Bioinformatics | Genetic Engineering | Metabolomics | News | Paper Summary | Proteomics | Tools | Transcriptomics | Trending
Scientists Introduce an Automated Pipeline ‘Galaxy-SynBioCAD’ for Synthetic Biology Design and Engineering
BySrishti Sharma September 6, 2022October 22, 2026
A toolshed for synthetic biology, metabolic engineering, and industrial biotechnology is available through the Galaxy-SynBioCAD portal. Using the tools and workflows available on the portal, one can create libraries of strains that produce the desired chemical targets, spanning a comprehensive metabolic pathway design and engineering process from selecting strains and targets, designing DNA parts to…
Read More Scientists Introduce an Automated Pipeline ‘Galaxy-SynBioCAD’ for Synthetic Biology Design and Engineering
Bioinformatics | Covid-19 News | Machine Learning | News | Paper Summary | SARS-CoV-2 | Trending
Deep Mutational Learning Determines the Impact of SARS-CoV-2 Receptor Binding Domain Mutations on Binding and Antibody Escape
BySrishti Sharma September 3, 2022September 3, 2022
It is highly likely that the COVID-19 pandemic will last longer due to the continuous evolution of SARS-CoV-2 and the emergence of variants that are resistant to vaccines and neutralizing antibodies. The ACE2 receptor-binding domain (RBD), a prime target site for neutralizing antibodies, plays a significant role in the selection and emergence of SARS-CoV-2 variants….
Read More Deep Mutational Learning Determines the Impact of SARS-CoV-2 Receptor Binding Domain Mutations on Binding and Antibody Escape
AI | Bioinformatics | Cancer Research | Cloud Computing | Data Science | Facts | Featured | Health | Machine Learning | News | Trending
Top Five Data Science Technologies Transforming Cancer Research
ByDr. Tamanna Anwar September 2, 2022October 22, 2026
Cancer is a disease that affects millions of people worldwide. According to the World Health Organization (WHO), cancer is the second leading cause of death globally, after cardiovascular diseases. In 2018, about 9.6 million deaths were reported due to cancer. The WHO estimates that over 1.8 million people died from cancer in 2017. The number…
Read More Top Five Data Science Technologies Transforming Cancer Research
Bioinformatics | COVID-19 | Covid-19 News | News | Paper Summary | SARS-CoV-2 | Tools | Trending
Epitope-Evaluator: A Shiny/R-based Web Tool for Interactively Analysing Predicted T-cell Epitopes
BySrishti Sharma September 1, 2022September 1, 2022
T-cell epitopes are predicted based on amino acid sequences of proteins from different MHC alleles using multiple immunoinformatic tools. Many of these tools produce hundreds of potential peptide candidates, but they are either non-graphical or unfriendly to non-programmers. Epitope-Evaluator is a web application developed in the Shiny/R framework for analyzing predicted T-cell epitopes interactively. A…
Read More Epitope-Evaluator: A Shiny/R-based Web Tool for Interactively Analysing Predicted T-cell Epitopes
Bioinformatics | Deep Learning | Machine Learning | News | Paper Summary | Trending
Self-supervised Deep Learning Algorithm “Cytoself” Provides High-Resolution Features of Protein Subcellular Localization
BySrishti Sharma August 30, 2022August 30, 2022
Understanding cellular architecture requires understanding the diversity and complexity of protein localization. The present study aims to introduce cytoself, a deep-learning approach that allows self-supervised profiling and clustering of protein localization. A self-supervised training scheme is leveraged by Cytoself, which requires no preexisting knowledge or categories. Using images of 1,311 endogenously labeled proteins from the…
Read More Self-supervised Deep Learning Algorithm “Cytoself” Provides High-Resolution Features of Protein Subcellular Localization
AI | Bioinformatics | Cancer Research | Deep Learning | Health | News | Trending
Clinical Validation of Deep Learning Algorithm to Simplify Lung Cancer Radiotherapy Treatment
ByDr. Tamanna Anwar August 29, 2022August 29, 2022
Nearly half of the cases of the most common cancer worldwide, lung cancer, are treated with radiation therapy (RT). RT planning is a time-consuming, resource-intensive process that can take days to weeks to complete, and even highly trained doctors disagree on how much tissue to target with radiation. Furthermore, as cancer rates rise, a global…
Read More Clinical Validation of Deep Learning Algorithm to Simplify Lung Cancer Radiotherapy Treatment
Algorithm | Bioinformatics | Machine Learning | News | RNA-Seq | Trending
Kyoto University Scientists Integrated Probability Algorithms within a Pocket-sized Sequencing Device to Read RNA Modifications More Precisely
ByDr. Tamanna Anwar August 28, 2022August 28, 2022
Scientists at Kyoto University introduced two new approaches that could help better distinguish RNA modifications affecting how genetic code is read using sequencing technology. The researchers are getting closer to identifying RNA sequence changes that affect protein formation and can cause diseases. The method, which was published in the journal Genomics, combines probability algorithms with…
Read More Kyoto University Scientists Integrated Probability Algorithms within a Pocket-sized Sequencing Device to Read RNA Modifications More Precisely
Bioinformatics | Cancer Research | News | NGS | Paper Summary | RNA-Seq | Trending
UCI Scientists Track Transposable Elements ‘Parasitic Genes’ in the Search for Disease Treatments
BySrishti Sharma August 27, 2022August 27, 2022
Scientists at the University of California, Irvine, provide new insights into “parasitic genes” or transposable elements. Despite accounting for more than half of human DNA, there is still much to learn about these elements. The new perspective could one day aid in the fight against cancer and aging-related diseases. The transposable element (TE) is an…
Read More UCI Scientists Track Transposable Elements ‘Parasitic Genes’ in the Search for Disease Treatments
AI | Bioinformatics | Computational Models | Neural Network | News | Paper Summary | Trending
MIT’s Artificial Intelligence Model Detects Parkinson’s Disease from Nocturnal Breathing Patterns
BySrishti Sharma August 25, 2022August 25, 2022
Scientists from MIT developed a device resembling a Wi-Fi router that employs a neural network to detect the presence and severity of the most rapidly growing neurological disease in the world, Parkinson’s disease. Parkinson’s disease (PD) affects more than 1 million Americans as of 2020, causing $52 billion in economic costs each year. Drugs have…
Read More MIT’s Artificial Intelligence Model Detects Parkinson’s Disease from Nocturnal Breathing Patterns
Bioinformatics | Health | News | Trending
Interactome of the Dementia Protein ‘Tau Protein’ Reveals its Role in Normal Memory
ByDr. Tamanna Anwar August 24, 2022December 28, 2022
According to new research from Flinders University, the tau protein, which plays a critical role in the development of Alzheimer’s disease, is also involved in normal learning processes in the healthy brain, potentially providing a target for future drug therapies. The researchers discovered that the tau protein, whose role has long been unknown, may aid…
Read More Interactome of the Dementia Protein ‘Tau Protein’ Reveals its Role in Normal Memory
Bioinformatics | Genetic Engineering | Infectious Diseases | News | Paper Summary | Trending
MIT Researchers used Multicellular Interface Patterning Based on 4-bit Adhesion Logic to Self-assemble Bacterial Systems into Desired 2D Shapes
BySrishti Sharma August 23, 2022August 23, 2022
A research team led by the professors at MIT and the University of Arizona has developed an experiment-theory platform for programming bacterial systems to grow into arbitrary two-dimensional target structures using genetically engineered bacteria and mathematical modeling. Multicellular systems, such as bacterial biofilms and human organs form interfaces (or boundaries) between different cell collectives to…
Read More MIT Researchers used Multicellular Interface Patterning Based on 4-bit Adhesion Logic to Self-assemble Bacterial Systems into Desired 2D Shapes

Cookie	Duration	Description
cookielawinfo-checkbox-analytics	11 months	This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".
cookielawinfo-checkbox-functional	11 months	The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".
cookielawinfo-checkbox-necessary	11 months	This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
cookielawinfo-checkbox-others	11 months	This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.
cookielawinfo-checkbox-performance	11 months	This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".
viewed_cookie_policy	11 months	The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data.

Bioinformatics

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

Predicting Genome-Wide Chromatin Loop using Deep Learning Model ‘DLoopCaller’

MIT Biologists Develop a New Computational Approach to Gain Insights into Repetitive Protein Sequences

Training

Services

Resources

Company