AI | Cell | News | Paper Summary | Proteomics | Trending

Fast and Accurate Imaging of Proteins in Cells with TomoTwin: A Novel AI-based Software
ByBanhita Maitra May 18, 2023May 21, 2023

Scientists from the Max Planck Institute of Molecular Physiology, Germany, have developed a method, TomoTwin, an open-source general picking model for cryogenic-electron tomograms. The method is based on deep metric learning and incorporates the embedding of tomograms in an information-rich, high-dimensional space that separates macromolecules according to their three-dimensional structures. The localization of particles within…

Read More Fast and Accurate Imaging of Proteins in Cells with TomoTwin: A Novel AI-based Software
AI | Chronic Diseases | Health | News | Trending

A New Era of Healthcare: Discover the Potential of Smartwatches in Chronic Disease Prevention
ByDr. Tamanna Anwar May 17, 2023December 22, 2023

The University of Queensland researchers have developed a comprehensive plan outlining the integration of smartwatches into Australia’s healthcare system. However, the researchers agree that significant obstacles must be solved before this becomes a reality. A significant change in how we monitor our health and general well-being has resulted from recent technological advancements. The smartwatch is…

Read More A New Era of Healthcare: Discover the Potential of Smartwatches in Chronic Disease Prevention
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Tools | Trending

Meet Foldseek: A High-Performance Deep Learning Approach for Fast and Accurate Protein Structure Search
ByBanhita Maitra May 16, 2023May 21, 2023

Scientists from Seoul National University, South Korea, and the Max Planck Institute for Multidisciplinary Sciences, Germany, have developed a deep learning-based method called Foldseek, which is a highly accelerated and accurate method for searching protein structures. Technological advances in structure prediction methods have yielded millions of protein structures, thus creating a bottleneck for searching operations…

Read More Meet Foldseek: A High-Performance Deep Learning Approach for Fast and Accurate Protein Structure Search
Bioinformatics | Cancer Research | News | Trending

Jumping Genes Could Transform Cancer Treatment with Innovative Immunotherapies
ByDr. Tamanna Anwar May 15, 2023December 12, 2023

The genetic mechanisms underlying cancer have been the focus of research by scientists and medical professionals worldwide. The human genome has undergone random insertions of small DNA fragments known as “jumping genes” during the history of evolution. Transposable elements, another name for these specific DNA pieces, have been linked to the development and spread of…

Read More Jumping Genes Could Transform Cancer Treatment with Innovative Immunotherapies
AI | Bioinformatics | Cancer Research | COVID-19 | News | Structural Biology | Trending

AI-Driven 3D Modeling Sheds Light on ‘Postal Workers’ within Human Cells
ByDr. Tamanna Anwar May 14, 2023January 5, 2024

Artificial intelligence (AI) and cellular biology have combined to change several sectors, including the mapping and monitoring of cellular activity within the human body, as technology continues to improve at an unprecedented rate. In a quest for a deeper understanding of conditions such as dementia and infectious diseases like COVID-19, scientists at IMB applied artificial…

Read More AI-Driven 3D Modeling Sheds Light on ‘Postal Workers’ within Human Cells
Bioinformatics | Health | Machine Learning | News | Paper Summary | Precision Medicine | Trending

Machine Learning-aided Auditory Categorization Model Decodes How Brains Recognize Communication Sounds
ByBanhita Maitra May 13, 2023May 13, 2023

Neuroscientists from the University of Pittsburgh extend a previously developed hierarchical model of auditory categorization by including several adaptive neural mechanisms that aid auditory categorization. Humans and animals need to generalize over the vast variability of communication sounds for robust auditory perception. The variability arises at both the level of production of sound as well…

Read More Machine Learning-aided Auditory Categorization Model Decodes How Brains Recognize Communication Sounds
Bioinformatics | Cancer Research | Disease Diagnosis | Medical Informatics | News | Trending

Meet Trumpet: The Biocomputing Platform Set to Transform Medicine
ByDr. Tamanna Anwar May 12, 2023May 12, 2023

The emerging field of biocomputing holds immense promise for transforming both the realms of computing and medicine. With its potential applications ranging from early detection and treatment of diseases to futuristic enhancements of human memory, biocomputing represents a groundbreaking avenue for medical research. However, conventional computer hardware has certain limitations when it comes to interacting…

Read More Meet Trumpet: The Biocomputing Platform Set to Transform Medicine
Bioinformatics | Deep Learning | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Trending

Improving Protein Binder Design: A Tenfold Leap with Deep Learning
ByBanhita Maitra May 11, 2023October 22, 2026

Scientists from the University of Washington, USA, studied how deep learning boosts and improves de novo protein binder design and devised a protocol for deep learning-aided protein binder design. In recent times, it has been plausible to design novel high-affinity protein-binding proteins using the structural information of the target alone. However, given the low success…

Read More Improving Protein Binder Design: A Tenfold Leap with Deep Learning
AI | Big Data | Bioinformatics | Health | News | Paper Summary | Trending

Google Unveils REMEDIS: A Self-Supervised Learning Approach for Robust and Enhanced Medical Imaging
BySipra Das May 10, 2023May 21, 2023

Recent achievements in the field of artificial intelligence (AI) have helped to develop effective medical imaging frameworks that can achieve professional clinical expertise. However, they often generated inadequate outputs while assessing clinical data, which was different from the training data. Google researchers and collaborators at the Georgia Institute of Technology and Northwestern University have proposed a new…

Read More Google Unveils REMEDIS: A Self-Supervised Learning Approach for Robust and Enhanced Medical Imaging
Bioinformatics | Cancer Research | Drug Discovery | News | NGS | Paper Summary | RNA-Seq | Trending

Discover How Single-cell RNA Sequencing is Transforming the Drug Discovery and Development Landscape
BySipra Das May 8, 2023May 8, 2023

The primary objective of modern proteomics studies is to analyze and isolate the proteome of individual cells from a pool of similar cells. Existing techniques like RNA sequencing, microarrays, quantitative PCR, and reverse transcription-PCR (qRT-PCR) are designed to analyze RNA in a population of cells in general. These techniques fail to quantify phenotypically different individual…

Read More Discover How Single-cell RNA Sequencing is Transforming the Drug Discovery and Development Landscape
Bioinformatics | Chemoinformatics | Drug Discovery | News | Paper Summary | Trending

Revolutionizing Fragment-based Drug Discovery: An Automated, Open-Source Workflow for Generating 3D Fragment Libraries
ByBanhita Maitra May 6, 2023October 22, 2026

Scientists from Amsterdam, Netherlands, have developed an automated and open-source workflow for the design of 3D fragment libraries in the KNIME software. Fragment-based drug discovery (FBDD) has proven successful in producing a growing list of clinical candidates, with six approved drugs as of 2022. Fragments, or smaller molecules, are used as screening compounds as opposed…

Read More Revolutionizing Fragment-based Drug Discovery: An Automated, Open-Source Workflow for Generating 3D Fragment Libraries
Algorithm | Bioinformatics | Genomics | News | Paper Summary | Sequencing | Trending

Meet OrthoVenn3: A Powerful, Web-based Platform for Analyzing and Visualizing Orthologous Data Across Genomes
BySipra Das May 5, 2023May 7, 2023

Recent developments in comparative genomics studies, along with the availability of cutting-edge computational tools, have revived the study of evolutionary biology and genetics in a new way. Existing computational tools can efficiently interpret orthologous clusters of genes and determine phylogenetic relationships among species. The recently upgraded release of the Web-based program OrthoVenn, called OrthoVenn3, with…

Read More Meet OrthoVenn3: A Powerful, Web-based Platform for Analyzing and Visualizing Orthologous Data Across Genomes
AI | Bioinformatics | News | NGS | OMICS | Paper Summary | RNA-Seq | Sequencing | Trending

Meet scGPT: A Cutting-edge Foundation Model for Single-cell Multiomics using Generative AI
ByBanhita Maitra May 4, 2023November 23, 2023

Scientists from the University of Toronto, Canada, have developed a foundation model for single-cell analysis, scGPT, by generative pre-training on over ten million cells. The generative pre-trained transformer for single-cell analysis is capable of capturing meaningful and crucial biological insights at the gene and cellular levels. The foundation model can be finetuned for numerous downstream…

Read More Meet scGPT: A Cutting-edge Foundation Model for Single-cell Multiomics using Generative AI
Algorithm | Bioinformatics | GWAS | Health | Medical Informatics | News | Paper Summary | Trending

Broad’s Scientist Introduce a Machine Learning Model to Identify Genetic Factors for Cardiovascular Diseases
BySipra Das May 3, 2023May 7, 2023

Using the heart as an investigational model, scientists at the Broad Institute of MIT and Harvard have designed an autoencoder-based machine-learning pipeline that can effectively predict a patient’s heart condition based on image data from ECGs and MRIs. The approach could also be used to detect markers related to cardiovascular diseases. Nearly all areas of…

Read More Broad’s Scientist Introduce a Machine Learning Model to Identify Genetic Factors for Cardiovascular Diseases
AI | Bioinformatics | Deep Learning | News | Paper Summary | Trending

Deep Learning Aided Image-Based Plant Phenotyping: A Benchmarking Study of Self-Supervised Contrastive Learning Methods
ByBanhita Maitra May 2, 2023May 2, 2023

Scientists from the University of Saskatchewan, Canada, have performed a benchmarking analysis of the self-supervised contrastive learning methods used in image-based plant phenotyping. Plant phenotyping, traditionally performed manually, is now being handed over to deep learning-based methods. However, there is still a scarcity of methods for plant phenotyping tasks such as detection and counting. The…

Read More Deep Learning Aided Image-Based Plant Phenotyping: A Benchmarking Study of Self-Supervised Contrastive Learning Methods
AI | Bioinformatics | COVID-19 | Deep Learning | News | Paper Summary | Proteomics | SARS-CoV-2 | Trending

De Novo Protein Interaction Design from Protein Surface Fingerprints using a Geometric Deep Learning Model ‘MaSIF-seed’
BySipra Das May 1, 2023May 7, 2023

The molecular surface of a protein is represented in the form of geometric and chemical attributes that create the unique fingerprint for identifying protein interaction. Geometric deep-learning-based algorithms can be used to analyze these fingerprints, which can help researchers design new computational tools to study Protein interactions. Inferring protein-protein interactions (PPIs) solely from their structural…

Read More De Novo Protein Interaction Design from Protein Surface Fingerprints using a Geometric Deep Learning Model ‘MaSIF-seed’
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Paper Summary | Structural Biology | Trending

Reshaping the Process of Drug Discovery: The Power of AI and Virtual Libraries in Giga-scale Screening
ByBanhita Maitra April 30, 2023October 22, 2026

Scientists from the University of Southern California, USA, shed light on the computational approaches that are transforming the drug discovery process from computer-aided to computer-driven. The flood of data about ligand properties and binding to therapeutic targets, coupled with their 3D structures, has revolutionized the drug discovery methodology. The advancement of computing capacities and the…

Read More Reshaping the Process of Drug Discovery: The Power of AI and Virtual Libraries in Giga-scale Screening
Algorithm | Bioinformatics | Cell | Computational Models | Machine Learning | News | Paper Summary | Trending

Meet MitoTNT: A Novel Approach for Tracking Mitochondrial Temporal Network in 4D Live-cell Fluorescence Microscopy Data
BySipra Das April 29, 2023April 30, 2023

Advancements in fluorescence microscopy-based imaging techniques have made it possible for researchers to view and analyze mitochondrial networks in 4D. Researchers at UCSD have released a new software called MitoTNT that utilizes fluorescence microscopy data to track mitochondrial time-varying networks. The efficiency of mitochondrial network tracking depends on the quality of the image generated by…

Read More Meet MitoTNT: A Novel Approach for Tracking Mitochondrial Temporal Network in 4D Live-cell Fluorescence Microscopy Data
AI | Big Data | Bioinformatics | Cell | News | Paper Summary | Trending

Streamlining Single-Cell RNA-Seq Analysis with OpenAI’s GPT-4: Reference-Free and Affordable Automated Cell Type Annotation
ByBanhita Maitra April 28, 2023April 28, 2023

Scientists from Columbia University, New York, have reported the possibility of automated cell type annotation in single-cell RNA seq (scRNA-seq) analysis using GPT-4, a chatbot. While cell type annotation is a significant step in the pipeline of sc-RNAseq analysis, it is often time-consuming and requires manual annotation using canonical marker genes. Automated cell-type annotation typically…

Read More Streamlining Single-Cell RNA-Seq Analysis with OpenAI’s GPT-4: Reference-Free and Affordable Automated Cell Type Annotation
Bioinformatics | Machine Learning | News | Paper Summary | Proteomics | Systems Biology | Trending

Bridging the Gap Between Proteomics and Systems Biology with ProInfer: A Machine Learning-based Approach for Protein Inference Analysis
BySipra Das April 27, 2023October 22, 2026

Protein identification has gained much importance over the last few years. In the shotgun proteomics-based approach, peptide fragments are used to identify proteins. The quantification of proteins from identified peptides is a difficult task. Scientists have suggested ProInfer, a new machine learning-based approach for performing Protein Inference based on biological networks. Mass Spectrometry (MS)-based Proteomics…

Read More Bridging the Gap Between Proteomics and Systems Biology with ProInfer: A Machine Learning-based Approach for Protein Inference Analysis
Bioinformatics | Cancer Research | News | Paper Summary | Precision Medicine | Transcriptomics | Trending

New Insights into the Etiologies of Early-Onset Colorectal Cancer Through an Integrative Multi-Omics Study
ByDiyan Jain April 26, 2023February 3, 2024

There is a growing number of incidences of colorectal cancer in people under the age of 50 (EOCRC), but the intrinsic molecular mechanisms underpinning it are not very well understood. A recent study was conducted on 79 CRC patients of Chinese ancestry to understand the differences in the omics of EOCRC compared to general CRC….

Read More New Insights into the Etiologies of Early-Onset Colorectal Cancer Through an Integrative Multi-Omics Study
AI | Bioinformatics | Computational Models | Deep Learning | Drug Discovery | News | Paper Summary | Structural Biology | Trending

Accurate Prediction of Protein Binding Interfaces with PeSTo: A Parameter-free Geometric Deep Learning Model
BySipra Das April 25, 2023April 25, 2023

Advancement in the field of genome sequencing has seen an increase in the amount of sequence data. In spite of that knowledge regarding the properties of protein still needs to be interpreted. Machine learning methods, particularly deep learning methods, are used to train language models to predict protein properties. A recent addition to the existing…

Read More Accurate Prediction of Protein Binding Interfaces with PeSTo: A Parameter-free Geometric Deep Learning Model
Bioinformatics | Drug Discovery | Machine Learning | News | Trending

Meet MF-PCBA: Multi-fidelity High-Throughput Screening Benchmarks for Drug Discovery and ML
ByBanhita Maitra April 24, 2023October 22, 2026

Scientists from the University of Cambridge present Multifideity PubChem Bioassay, MF-PCBA, a collection of 60 molecular datasets with multiple modalities, reflecting the real-world nature of HTS (high-throughput screening) projects in drug discovery. MF-PCBA is a curated collection of datasets with two data modalities for each dataset, viz., primary and confirmatory screening, termed multi-fidelity. Previously, the…

Read More Meet MF-PCBA: Multi-fidelity High-Throughput Screening Benchmarks for Drug Discovery and ML
Bioinformatics | Genomics | Metagenomics | News | OMICS | Paper Summary | Trending

New Study Reveals Extensive Person-to-Person Gut and Oral Microbiome Transmission Landscape
ByDiyan Jain April 23, 2023April 23, 2023

The human microbiome is an essential aspect of the human body and could be responsible for several health conditions. Yet, much of microbiome transmission within and across populations and how that shapes an individual’s microbiome’s genetic makeup.is still to be understood. A recent paper in nature explores the transmission patterns of the gut and oral…

Read More New Study Reveals Extensive Person-to-Person Gut and Oral Microbiome Transmission Landscape
AI | Bioinformatics | COVID-19 | Covid-19 News | Health | Machine Learning | News | Paper Summary | SARS-CoV-2 | Trending

Long-Term Protection from COVID-19: The Promise of T-Cell Vaccines Designed using Machine Learning Platform ‘RAVEN’
ByBanhita Maitra April 21, 2023April 22, 2023

Scientists from Denmark and Pennsylvania have developed a machine learning-based platform, RAVEN, that is able to design T-cell vaccines for COVID-19. These vaccines are expected to last longer than the currently available ones, thereby providing immunity against future variants of concern (VOCs). The in-silico approach for locating and selecting relevant immunogenic T-cell regions in the SARS-Cov-2 genome…

Read More Long-Term Protection from COVID-19: The Promise of T-Cell Vaccines Designed using Machine Learning Platform ‘RAVEN’
Bioinformatics | Disease Diagnosis | News | Paper Summary | RNA-Seq | Sequencing | Trending

Pediatric Rare Disease Diagnosis using Trio RNA Sequencing
BySipra Das April 20, 2023April 20, 2023

The RNA-Seq (RNA sequencing) program at The Hospital for Sick Children (SickKids) is focused on developing new tools for Pediatric Rare Disease research. Their clinically approved RNA sequencing platform combines RNA and Genome sequencing methods to create personalized medicine. The study also reviewed the applicability of Trio RNA sequencing methods in identifying mutations causing inherited diseases in…

Read More Pediatric Rare Disease Diagnosis using Trio RNA Sequencing
Bioinformatics | Drug Discovery | Structural Biology | Trending

Transforming Drug Discovery with BEAR: A New Virtual Screening Approach Utilizing Large-Scale Bioactivity Data
ByDiyan Jain April 19, 2023October 22, 2026

Data-driven drug discovery provides an effective path for drug development using large bioassay datasets containing the bioactivity profiles of millions of compounds. Recently, researchers have developed BEAR (Bioactive compound Enrichment by Assay Repositioning), a novel method of finding potential drug candidates by exploiting those bioassay datasets. BEAR can discover a diverse range of potential dr…

Read More Transforming Drug Discovery with BEAR: A New Virtual Screening Approach Utilizing Large-Scale Bioactivity Data
AI | Bioinformatics | Disease Diagnosis | GWAS | Health | News | Trending

Deep Learning on Retinal Images: Google’s Aging Clock ‘eyeAge’ Unlocks the Secrets of Aging
ByBanhita Maitra April 18, 2023April 18, 2023

Google scientists have developed a novel aging clock based on retinal images using deep learning techniques called “eyeAge.” The biological clock is often said to vary from chronological age for an individual and has been previously studied extensively using predictive aging clocks based on biomarkers such as DNA methylation. These often require blood samples and…

Read More Deep Learning on Retinal Images: Google’s Aging Clock ‘eyeAge’ Unlocks the Secrets of Aging
AI | Bioinformatics | News | Paper Summary | Trending

Unleashing the Power of OpenAI’s ChatGPT for Solving Bioinformatics Programming Tasks
ByDiyan Jain April 17, 2023April 17, 2023

Computer programming is crucial for life scientists, as it enables them to perform many essential research tasks. However, learning to code can be challenging for life science students and researchers. Recently, a study evaluated the effectiveness of one large language model (LLM), ChatGPT, in completing basic-to-moderate-level programming exercises from an introductory bioinformatics course. The results…

Read More Unleashing the Power of OpenAI’s ChatGPT for Solving Bioinformatics Programming Tasks
AI | Bioinformatics | Health | Medical Informatics | News | Trending

Google Introduces Med-PaLM 2: An AI-based Medical Language Model for Comprehensive Medical Query Responses
BySipra Das April 16, 2023December 19, 2023

Google has made significant advancements in the field of AI-based medical technology with the launch of Med-PaLM 2, a limited-access tool that utilizes the medical language learning model (LLM). Med-PaLM 2 is designed to accurately answer medical questions, marking a major breakthrough in the field. Google also launched its Cloud-Based Claims Acceleration Suite to speed…

Read More Google Introduces Med-PaLM 2: An AI-based Medical Language Model for Comprehensive Medical Query Responses
Algorithm | Bioinformatics | Covid-19 News | News | Paper Summary | Phylogenetic Analysis | SARS-CoV-2 | Tools | Trending

EMBL-EBI Researchers Develop a Phylogenetic Tool ‘MAPLE’ to Uncover Insights from Pandemic-scale Genome Data
BySipra Das April 15, 2023May 21, 2023

The rapid influx of large genomic data during the recent pandemic caused by COVID-19 constrained the researcher’s ability to analyze vast microbial genomes at once due to the lack of faster and more powerful tools. Researchers at EMBL-EBI have recently come forward with a robust bioinformatics tool MAPLE which efficiently reduces the size of bulky genomic data….

Read More EMBL-EBI Researchers Develop a Phylogenetic Tool ‘MAPLE’ to Uncover Insights from Pandemic-scale Genome Data
Bioinformatics | Cell | Gene Expression | News | Paper Summary | RNA-Seq | Transcriptomics | Trending

Tracking Gene Expression Changes in Single Cells over Time and Space with TEMPOmap
ByBanhita Maitra April 14, 2023December 28, 2023

Scientists from the Broad Institute of MIT and Harvard have developed TEMPOmap, a method that unravels subcellular RNA profiles spatiotemporally at the single-cell level. The method incorporates pulse-chase metabolic labeling and multiplexed-three dimensional in situ sequencing for simultaneous profiling of the age and location of individual RNAs. The authors discovered kinetic gene clusters while performing RNA kinetic…

Read More Tracking Gene Expression Changes in Single Cells over Time and Space with TEMPOmap
Big Data | Bioinformatics | Genomics | News | Paper Summary | Tools | Trending

Uncovering Biological Applications of Julia: A Programming Language with Incredible Speed, Abstraction, and Metaprogramming Abilities
ByDiyan Jain April 13, 2023April 14, 2023

As researchers gather increasingly complex and extensive data, it is also becoming increasingly difficult to accurately and efficiently process and analyze everything. Julia, a relatively new programming language, presents unique benefits and features, making it an ideal solution for this challenge. Its three key features make it stand out from other existing languages, i.e., speed,…

Read More Uncovering Biological Applications of Julia: A Programming Language with Incredible Speed, Abstraction, and Metaprogramming Abilities
Bioinformatics | Genomics | Infectious Diseases | News | Paper Summary | SARS-CoV-2 | Trending

Extracting Specific and Sensitive Biomarkers from Massive Microbial Genomic Datasets with SHINE: A Novel Approach
BySipra Das April 13, 2023April 13, 2023

Shine is a computational approach for extracting distinct, well-conserved biomarkers from a large dataset of the microbial genome. The method has been clinically tested and showed promising results in detecting all pathogenic microorganisms with lower false positives or false negatives rates. Shine utilizes a two-directional approach to identify consensus sequences by identifying distinct regions or…

Read More Extracting Specific and Sensitive Biomarkers from Massive Microbial Genomic Datasets with SHINE: A Novel Approach
AI | Bioinformatics | Cancer Research | Health | News | Paper Summary | Trending

Single-cell Based AI Pathologist for Rapid Physical Phenotyping of Cancer Biopsies
ByBanhita Maitra April 12, 2023April 12, 2023

Scientists from the Max Planck Institute for the Science of Light, Germany, have developed a novel methodology for rapid pathological analysis of cells from cancerous tissue samples using artificial intelligence and a single-cell approach. This methodology is capable of generating tumor biopsy analysis results in as early as 30 minutes, enabling intra-operative consultation pathology, which…

Read More Single-cell Based AI Pathologist for Rapid Physical Phenotyping of Cancer Biopsies
Bioinformatics | Cancer Research | Drug Discovery | News | Paper Summary | Sequencing | Trending

Efficiently Identifying Bispecific Antibodies using High Throughput Single-cell BsAb Discovery Pipeline
ByDiyan Jain April 11, 2023January 18, 2024

Bispecific antibodies (BsAbs) are an emerging type of immunotherapy and have great potential to treat various diseases. Recently, researchers have developed a novel single-cell platform that can efficiently discover rare BsAb clones with unique and desirable properties that would otherwise be close to impossible to discover using other existing conventional low-throughput, biased, and trial-and-error methods….

Read More Efficiently Identifying Bispecific Antibodies using High Throughput Single-cell BsAb Discovery Pipeline
Bioinformatics | News | NGS | Paper Summary | RNA-Seq | Transcriptomics | Trending

Overcoming Challenges in Detecting and Quantifying Splicing Variations in Large RNAseq Datasets with MAJIQ v2
ByBanhita Maitra April 10, 2023April 10, 2023

Scientists from UPenn have developed a suite of tools and algorithms for analyzing heterogeneous and large RNAseq datasets for detecting, quantifying, and visualizing the splicing variations therein. The suite of algorithms and tools is present as a part of the package MAJIQ version 2. The former MAJIQ (Modeling Alternative Junction Inclusion Quantification) package was developed…

Read More Overcoming Challenges in Detecting and Quantifying Splicing Variations in Large RNAseq Datasets with MAJIQ v2
Bioinformatics | Genomics | News | NGS | Paper Summary | Tools | Trending

KCL Researchers Develop DNAscan2: A Highly Flexible, End-to-End Pipeline for NGS Data Analysis
ByDiyan Jain April 9, 2023January 7, 2024

Next-generation sequencing (NGS) is becoming increasingly accessible and affordable, illustrating its growing importance and adoption in the field of clinical and biomedical genetics. To keep up with this growth, King’s College London researchers have developed DNAscan2, a novel, user-friendly, end-to-end pipeline for analyzing NGS data. The software’s versatility, scalability, and the fact that it is…

Read More KCL Researchers Develop DNAscan2: A Highly Flexible, End-to-End Pipeline for NGS Data Analysis
Bioinformatics | Genomics | News | OMICS | Paper Summary | Precision Medicine | Trending

Transforming Functional Genomics Research using EN-TEx: A Resource of Multi-tissue Epigenomes & Variant-Impact Models
ByDiyan Jain April 8, 2023January 7, 2024

Recently, a paper published on Cell reports the EN-TEx, a system/project that challenges conventional functional genomics research by providing a comprehensive resource that goes beyond the use of a single haploid reference genome. The resource contains information on personal epigenomes and associated models that could be combined with other genome annotation resources. By utilizing the…

Read More Transforming Functional Genomics Research using EN-TEx: A Resource of Multi-tissue Epigenomes & Variant-Impact Models
Bioinformatics | Database | Genomics | Infectious Diseases | News | Paper Summary | Trending

Recent Research Unveils New Genomic Landscape of the Human Gut Microbiome
ByBanhita Maitra April 7, 2023April 7, 2023

Scientists from BGI-Research developed a new version of the Cultivated Genome Reference (CGR), a repository of high-quality draft genomes of the human gut microbiome. The current version of CGR, which is CGR2, has been further expanded to incorporate numerous high-quality draft genomes generated from cultivated bacteria. CGR2 classifies previously unidentified species and uncovers the functional…

Read More Recent Research Unveils New Genomic Landscape of the Human Gut Microbiome
Bioinformatics | Machine Learning | News | Paper Summary | Trending

Using Virtual Reality-based Real-time Imaging to Unravel the Complexities of Autism’s Neural Network Dynamics
ByDiyan Jain April 6, 2023April 6, 2023

Neuropsychiatric disorders are a serious public health concern, given that they are the leading cause of disability and account for millions of deaths worldwide. Despite thorough research efforts during the past few years, our understanding of the complex biological mechanistic processes underlying these conditions remains mainly unknown. Recently, a study by researchers at RIKEN BSI…

Read More Using Virtual Reality-based Real-time Imaging to Unravel the Complexities of Autism’s Neural Network Dynamics
AI | Algorithm | Bioinformatics | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Trending

MIT’s DiffDock: A Breakthrough Diffusion Generative Model-based Approach for Molecular Docking
ByBanhita Maitra April 5, 2023April 6, 2023

Researchers at the Abdul Jameel Clinic for Machine Learning in Health, MIT, have developed a novel method, DiffDock, an accelerated drug discovery pipeline using a diffusion generative model (DGM)-based approach for molecular docking. One of the crucial processes involved in a drug design pipeline involves molecular docking, which predicts the binding structure of a ligand…

Read More MIT’s DiffDock: A Breakthrough Diffusion Generative Model-based Approach for Molecular Docking
Bioinformatics | News | NGS | OMICS | Paper Summary | Proteomics | RNA-Seq | Trending

Researchers Introduce PALMO: A Novel Software Platform for Longitudinal Multi-omics Data Analysis
ByDiyan Jain April 5, 2023April 5, 2023

In the past few years, there has been a significant increase in multi-omics data generation for biomedical research. However, the analysis of these large-scale, complex, and heterogeneous datasets represents an enormous challenge for researchers. Recently, researchers from the Allen Institute of Immunology have developed a ground-breaking PALMO platform, which contains five analytical modules allowing the…

Read More Researchers Introduce PALMO: A Novel Software Platform for Longitudinal Multi-omics Data Analysis
Bioinformatics | Drug Discovery | Machine Learning | Neural Network | News | Paper Summary | Structural Biology | Trending

Enhancing De Novo Drug Design with QADD: A Powerful Combination of Reinforcement Learning and Graph-based Molecular Quality Assessment
ByBanhita Maitra April 3, 2023October 22, 2026

Scientists from Shanghai have developed a de novo drug design method, QADD (quality assessment-based drug design approach). The multi-objective reinforcement learning-based method is capable of designing chemical molecules with desired properties using a novel Quality Assessment (QA) module. The novel drug design framework is able to cover a large territory of the chemical space that was previously…

Read More Enhancing De Novo Drug Design with QADD: A Powerful Combination of Reinforcement Learning and Graph-based Molecular Quality Assessment
Algorithm | Bioinformatics | Machine Learning | News | Paper Summary | Structural Biology | Trending

Precise Protein-Ligand-Binding Site Mapping with ‘SiteRadar’: A Graph Machine Learning Algorithm
BySejal Saxena April 2, 2023May 7, 2023

The identification of ligand-binding sites on the surface of a protein is a vital aspect of structure-based drug design. SiteRadar is a new algorithm for identifying ligand-binding sites on protein surfaces, which is important for structure-based drug design. It outperforms existing techniques, including machine learning algorithms, and can detect up to 74% of true ligand-binding…

Read More Precise Protein-Ligand-Binding Site Mapping with ‘SiteRadar’: A Graph Machine Learning Algorithm
AI | Bioinformatics | Deep Learning | Disease Diagnosis | Health | News | Trending

Why the Shape of Your Heart Could be the Key to a Longer and Healthier Life
ByDr. Tamanna Anwar April 1, 2023April 1, 2023

Recent findings by the Smidt Heart Institute based on deep learning analysis of medical images suggest, that one’s likelihood of developing atrial fibrillation and heart muscle disease can be predicted by the shape of their heart as well as certain genetic indicators. What Determines Heart Shape? It’s crucial to first understand what affects how your…

Read More Why the Shape of Your Heart Could be the Key to a Longer and Healthier Life
AI | Bioinformatics | Cancer Research | Computational Models | Disease Diagnosis | Machine Learning | News | Paper Summary | Trending

Researchers Offer an Innovative Single Test-Based Approach for Early Stage Cancer Diagnosis using Exosomes, SERS Technology, and AI
ByDiyan Jain April 1, 2023April 1, 2023

Conventionally, cancer diagnostic procedures have been known for their invasive nature and enormous cost. However, researchers from KAIST and Korea University have developed a novel diagnostic approach that combines AI and innovative technology for an affordable, accessible, and non-invasive diagnosis of multiple types of cancer at an early stage under high resolution. In the study,…

Read More Researchers Offer an Innovative Single Test-Based Approach for Early Stage Cancer Diagnosis using Exosomes, SERS Technology, and AI
Bioinformatics | Cancer Research | Machine Learning | News | Paper Summary | Structural Biology | Trending

LLNL Scientists Introduce Cutting-edge Theoretical Model for More Efficient Simulations of Cancer-linked Protein Interactions
ByBanhita Maitra March 31, 2023June 14, 2023

Lawrence Livermore National Laboratory, California’s scientists have developed a theoretical model based on Dynamic Density Functional Theory (DDFT) for modeling multicomponent cellular membranes as a continuum. The cellular membranes considered are composed of an arbitrary number of lipid types, and the continuum model for the cellular membranes is trained on molecular dynamics (MD) simulations. Within…

Read More LLNL Scientists Introduce Cutting-edge Theoretical Model for More Efficient Simulations of Cancer-linked Protein Interactions
Algorithm | Bioinformatics | Cancer Research | Deep Learning | News | Paper Summary | Trending

Evaluating the Efficacy of Deep Learning Algorithms for Predicting Drug Synergy in Cancer Treatment
BySejal Saxena March 30, 2023March 30, 2023

Cancer therapies often become ineffective due to the development of resistance in the tumor cells against the treatment. One potential strategy to overcome this resistance was treating the patients with a combination of drugs. Scientists conducted a study to improve cancer treatment by developing deep-learning models for drug synergy prediction. The models were designed to…

Read More Evaluating the Efficacy of Deep Learning Algorithms for Predicting Drug Synergy in Cancer Treatment
Bioinformatics | Computational Models | COVID-19 | Covid-19 News | Drug Discovery | Infectious Diseases | News | Paper Summary | Trending | Virus

Novel Workflow Uses Targeted Computer Modeling to Predict Druggable Targets Against SARS-CoV-2
ByBanhita Maitra March 29, 2023October 22, 2026

Scientists from the University of Tübingen, Germany, have developed a novel workflow for predicting robust druggable targets against emerging viral infections such as the SARS-CoV-2. The workflow implementation comprises pymCADRE and PREDICATE, which incorporate metabolic changes in infected cells for accelerated prediction of drug targets. The authors generated tissue-specific metabolic models, constructed viral biomass functions,…

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