Paper Summary

Plain-language summaries of new research papers in bioinformatics, computational biology and life sciences.

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 | 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
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
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 | 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 | 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
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
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)
AI | Algorithm | COVID-19 | Database | Drug Discovery | Paper Summary

Expediating the Discovery of Super Tight-Binding Antibodies with an AI Model “RESP”
ByBanhita Maitra February 3, 2023February 3, 2023

Scientists from UCSD have devised an efficient AI-based pipeline, RESP, for identifying high-affinity antibodies. Typically, researchers would employ directed evolution to enable iterative mutagenesis and selection to identify and assess high-affinity antibodies. Existing methods employing deep learning techniques fail to provide statistical estimates for assessing reliable predictions. RESP, as a pipeline, implements an autoencoder model…

Read More Expediating the Discovery of Super Tight-Binding Antibodies with an AI Model “RESP”
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
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…

Read More De Novo Drug Design Using Generative Deep Learning: Implementing Chemical Language Models with Molecular Structures and Bioactivity
Bioinformatics | Deep Learning | Machine Learning | News | Paper Summary | Structural Biology | Trending

ML meets Structural Bioinformatics: Novel Machine Learning Approaches Transforming Protein Research Landscape
ByBanhita Maitra January 25, 2023January 25, 2023

Scientists from University College London, UK, study the Machine Learning (ML) approaches that have successfully closed the ever-widening gap between large amounts of protein sequences produced by state-of-the-art sequencing methods and annotations of the structures and functions of proteins. One of the best methods for structure prediction, AlphaFold2 (AF2), has resulted in a 1,000-fold increase…

Read More ML meets Structural Bioinformatics: Novel Machine Learning Approaches Transforming Protein Research Landscape
AI | Bioinformatics | COVID-19 | Deep Learning | Drug Discovery | News | Paper Summary | Structural Biology | Trending

ImageMol – A Powerful Self-supervised Image Representation Learning Framework for Accurate Prediction of Molecular Properties and Drug Targets
ByCatherene Tomy January 19, 2023October 22, 2026

Scientists from Case Western Reserve University, Cleveland, USA, developed a self-supervised image representation learning framework, “ImageMol,” for predicting molecular properties and drug targets with high accuracy, making it a valuable tool for computational drug discovery. Imagine we belong to the incredibly lazy bunch that uses a pre-made pizza crust that would probably make every Italian…

Read More ImageMol – A Powerful Self-supervised Image Representation Learning Framework for Accurate Prediction of Molecular Properties and Drug Targets
Bioinformatics | Cancer Research | Computational Models | Machine Learning | News | OMICS | Paper Summary | Precision Medicine | RNA-Seq | Tools | Trending

CHESSBOARD: A Bayesian Approach to Identifying Cancer Subtypes through Unsupervised Detection of RNA Splicing
ByRiya Vishwakarma January 10, 2023January 20, 2023

Finding cancer subtypes is a crucial first step in creating individualized care. In particular, RNA splicing change-based sub-typing has been encouraged by a number of recent studies. An unsupervised technique called CHESSBOARD was developed by scientists in the USA specifically for RNA splicing data. It identifies “tiles” in the data that are identified by a…

Read More CHESSBOARD: A Bayesian Approach to Identifying Cancer Subtypes through Unsupervised Detection of RNA Splicing
Bioinformatics | Chronic Diseases | Genomics | GWAS | Health | News | OMICS | Paper Summary | Sequencing | Trending

Exploring the Intersection of Genomics and Phenomics in the Study of Body Mass Index Reveals a Complex Disease Network
ByRiya Vishwakarma January 8, 2023January 20, 2023

The relationship between Body Mass Index (BMI) and several health issues that have an influence on morbidity and mortality has been the focus of research by epidemiologists and scientists with roots in China and the USA. The possibility to further our understanding of the breadth and depth of illnesses connected to obesity exists in the…

Read More Exploring the Intersection of Genomics and Phenomics in the Study of Body Mass Index Reveals a Complex Disease Network
AI | Bioinformatics | Deep Learning | Metagenomics | News | OMICS | Paper Summary | Precision Medicine | Trending

Exploring Type 2 Diabetes Drug-Omics Associations Using Deep Learning Models
ByRiya Vishwakarma January 6, 2023January 20, 2023

Multiple omics technologies may be used in biological cohorts to identify patient-level disease features and unique treatment responses. The size and heterogeneity of the multi-modal data, however, constitute integrating and inference a challenging challenge. Multi-omics variational autoencoders (MOVE), a deep-learning-based framework created by researchers from the University of Copenhagen and Copenhagen Research Center, was used…

Read More Exploring Type 2 Diabetes Drug-Omics Associations Using Deep Learning Models
Bioinformatics | News | Paper Summary | Structural Biology | Trending

A Hidden Markov Modeling Approach for Estimating Orientations and Structures of Biomolecules from High-Speed Atomic Force Microscopy Time-Series Images
ByRiya Vishwakarma January 4, 2023January 20, 2023

Saitama University, Japan, researchers developed a powerful method for observing the time-resolved behavior of biomolecules through high-speed atomic force microscopy (HS-AFM), thus improving the approach for estimating structural information from AFM data. Deciphering dynamics of biomolecules The surface geometry of a sample molecule is the only structural information present in HS-AFM pictures, though. It is…

Read More A Hidden Markov Modeling Approach for Estimating Orientations and Structures of Biomolecules from High-Speed Atomic Force Microscopy Time-Series Images
AI | Bioinformatics | Cancer Research | Computational Models | Machine Learning | Neural Network | News | Paper Summary | Trending

Meet GCNCPR-ACPs: An Innovative Model for Predicting Anticancer Peptides Based on Graph Convolution Network
ByRiya Vishwakarma January 2, 2023January 2, 2023

Researchers at the School of Informatics, Xiamen University, China, and Computational Health Informatics Program, Boston Children’s Hospital, USA developed the GCNCPR-ACPs method to effectively capture different levels of node attributes for amino acid node representation learning. GCNCPR-ACPs (a Graph Convolution Neural Network Method is a new machine learning-based method based on collapse pooling and residual…

Read More Meet GCNCPR-ACPs: An Innovative Model for Predicting Anticancer Peptides Based on Graph Convolution Network
Bioinformatics | Computational Models | Deep Learning | Drug Discovery | Neural Network | News | Paper Summary | Trending

Unleashing the Power of Unsupervised Language Model and Triplet Neural Network Integration for Protein Gene Ontology Prediction
ByRiya Vishwakarma December 29, 2022October 22, 2026

To understand how living systems operate and develop new medications, it is essential to identify protein functions accurately. Researchers from the USA propose a new model, ATGO, for predicting Gene Ontology (GO) attributes of proteins using a triplet neural network that is enhanced with unsupervised language models trained on protein sequences. The integration of the…

Read More Unleashing the Power of Unsupervised Language Model and Triplet Neural Network Integration for Protein Gene Ontology Prediction
Bioinformatics | Cancer Research | Machine Learning | News | Paper Summary | Precision Medicine | RNA-Seq | Tools | Transcriptomics | Trending

Scientists Design Machine Learning Model to Decipher the Microenvironment Communication Networks of Individual Tumors
ByCatherene Tomy December 28, 2022December 28, 2022

Intercellular networks between key players in the tumor microenvironments make tumor cells invincible against the body’s natural defense mechanisms. Identifying and targeting these interactions can make tumors more susceptible to tumor invasions and their eventual retardation. This study demonstrates the use of Bayesian network models in designing a network that links together these interactions by…

Read More Scientists Design Machine Learning Model to Decipher the Microenvironment Communication Networks of Individual Tumors
Bioinformatics | News | NGS | OMICS | Paper Summary | RNA-Seq | Transcriptomics | Trending

Bioinformatics Approaches used in Single-cell Technologies: Recent Progress and Future Directions in Applied Research
ByRiya Vishwakarma December 20, 2022December 20, 2022

Researchers from China examined the experimental and bioinformatics approaches used in single-cell research as well as their applications in a variety of industries, thereby predicting future developments in single-cell technology. A growing number of single-cell technologies have been introduced in past years. Large-scale initiatives like the Human Cell Atlas, Mouse Cell Atlas, Mouse RNA Atlas,…

Read More Bioinformatics Approaches used in Single-cell Technologies: Recent Progress and Future Directions in Applied Research
Bioinformatics | Genomics | News | Paper Summary | RNA-Seq | Sequencing | Trending

Annotate_My_Genomes: A Simple Pipeline for Improved Genome Annotation and Neglected Gene Discovery Through Hybrid RNA Sequencing
ByRiya Vishwakarma December 19, 2022December 19, 2022

A simple genome-guided transcriptome annotation pipeline created by researchers from Chile and the University of Manitoba in Winnipeg, Manitoba, Canada, that takes compiled transcripts from hybrid sequencing information as input and recognizes coding and long non-coding RNAs by integrating a number of bioinformatic techniques, including gene reconciliation with earlier annotations in GTF format. The expansion…

Read More Annotate_My_Genomes: A Simple Pipeline for Improved Genome Annotation and Neglected Gene Discovery Through Hybrid RNA Sequencing
AI | Bioinformatics | Computational Models | Deep Learning | Drug Discovery | News | Paper Summary | Trending

Scientists Develop Deep Learning Models for RNA Degradation Prediction via Crowdsourcing, Critically Important for Stable RNA Therapeutics
ByCatherene Tomy December 18, 2022December 17, 2022

Scientists at the University of Stanford display the potential of crowdsourcing in accelerating and enhancing the research process. The study utilized two crowdsourcing platforms, Eterna and Kaggle, to design the RNA input and develop models that predict their degradation profile to aid in the design of stable mRNA therapeutics. The intrinsic instability that causes self-destruction…

Read More Scientists Develop Deep Learning Models for RNA Degradation Prediction via Crowdsourcing, Critically Important for Stable RNA Therapeutics
AI | Bioinformatics | Corona Virus | COVID-19 | Covid-19 News | Machine Learning | News | Paper Summary | SARS-CoV-2 | Trending

Researchers Develop a Machine Learning Model to Predict Whether a COVID-19 Test Might be Positive or Not
ByRiya Vishwakarma December 17, 2022December 17, 2022

A study from Florida Atlantic University used machine learning to provide new evidence for understanding how molecular tests and serology tests are correlated and what features are most useful in COVID-19 testing. This could be useful in helping healthcare providers prioritize testing and treatment for patients most likely to have the virus. Severe Acute Respiratory…

Read More Researchers Develop a Machine Learning Model to Predict Whether a COVID-19 Test Might be Positive or Not
Antibiotic Resistance | Bioinformatics | Cancer Research | News | Paper Summary | Proteomics | Trending

Pancreatic Cancer and Drug Resistance: Researchers Identify Key Metabolic Regulators
ByCatherene Tomy December 16, 2022December 16, 2022

Drug resistance can be countered only by interrupting the adaptive measures taken by the cells to deflect the drug action. Scientists from the School of Pharmacy and Pharmaceutical Sciences, University of Buffalo, performed an extensive study through proteomic analysis that identified key regulators driving the resistance against Gemcitabine, the principal chemotherapeutic against Pancreatic Adenocarcinoma. The…

Read More Pancreatic Cancer and Drug Resistance: Researchers Identify Key Metabolic Regulators
Bioinformatics | Cancer Research | Covid-19 News | Drug Discovery | Health | News | Paper Summary | RNA-Seq | Trending

Human Cell Atlas Mission: A Reference Map for Analyzing Human Health and Identifying, Tracking, and Treating Diseases
ByRiya Vishwakarma December 15, 2022October 22, 2026

In order to better understand human health and to identify, track, and cure diseases, the International Human Cell Atlas collaboration is building detailed reference maps of every human cell, which is life’s basic building block. The Human Cell Atlas aims to map every type of cell in the human body, revolutionizing how we understand biology…

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Bioinformatics | News | Paper Summary | RNA-Seq | Trending

Cell Type-Specific Differential Gene Expression: A Guide Through The Available Methods
ByCatherene Tomy December 14, 2022December 14, 2022

There is no one-size-fits-all approach to differential expression analysis, and the best method for a given dataset depends on the specific research question. Various cell type-specific methods are available, and it is important to choose the method that is appropriate for the data. Nine methods that analyze cell type-specific differential gene expression (csDEG) were compared…

Read More Cell Type-Specific Differential Gene Expression: A Guide Through The Available Methods

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Paper Summary

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