Deep Learning

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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
AI | Algorithm | Bioinformatics | Deep Learning | Disease Diagnosis | Health | News | Trending

Speech Analysis Meets Artificial Intelligence: The Promise of Deep Learning for Depression Detection
ByDr. Tamanna Anwar February 9, 2023February 9, 2023

Scientists at Jinhua Advanced Research Institute and Harbin University of Science and Technology have developed a deep-learning algorithm that can identify depression through speech. This algorithm was trained to recognize emotions in spoken language by looking at various pertinent traits. Millions of people all over the world go through depression, which is a common mental…

Read More Speech Analysis Meets Artificial Intelligence: The Promise of Deep Learning for Depression Detection
AI | Bioinformatics | Deep Learning | Disease Diagnosis | Health | News | Trending

The Future of Rare Disease Prediction: Machine Learning Takes the Lead
ByDr. Tamanna Anwar February 7, 2023February 7, 2023

The POPDx model does not require extensive patient datasets, which makes it potentially useful for patients with rare diseases. The POPDx framework was created to effectively identify a wide variety of phenotypes among participants in the UK Biobank study. To provide a thorough analysis, it makes use of a wide variety of patient data, including…

Read More The Future of Rare Disease Prediction: Machine Learning Takes the Lead
Bioinformatics | 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
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
AI | Bioinformatics | Biomedical Engineering | Computational Models | Deep Learning | Drug Discovery | Machine Learning | News | Proteomics | Trending

AI Proteins: Unlocking the Potential of Protein Generation from Scratch with Natural Language Model “ProGen”
ByDr. Tamanna Anwar January 28, 2023October 22, 2026

Scientists from the University of California, San Francisco, have created an inventive AI system that can create entirely new enzymes from scratch. Even though the amino acid sequences of these synthetic enzymes differ significantly from those of any naturally occurring protein, they have demonstrated remarkable efficacy in laboratory experiments. In other words, using state-of-the-art technology,…

Read More AI Proteins: Unlocking the Potential of Protein Generation from Scratch with Natural Language Model “ProGen”
Bioinformatics | 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 | Cancer Research | Computational Models | Deep Learning | News | Precision Medicine | Trending

Revolutionizing Healthcare: Federated Learning Deployed Across Hospitals to Train Deep Learning Models Securely
ByDr. Tamanna Anwar January 21, 2023January 21, 2023

Owkin, an AI biotech company, has successfully used federated learning (FL) for the first time to train deep learning models on histopathology data from multiple hospitals without the need for the data to be transferred outside of hospital security systems. This groundbreaking achievement was reported in a study published in Nature Medicine. The unveiling of this…

Read More Revolutionizing Healthcare: Federated Learning Deployed Across Hospitals to Train Deep Learning Models Securely
AI | Algorithm | Bioinformatics | Cancer Research | Chronic Diseases | Deep Learning | Disease Diagnosis | Documentaries | Neural Network | News | Precision Medicine | Trending

Deep Learning and Radiomics: A Game-changer for Identifying Glioblastoma and Brain Metastases
ByDr. Tamanna Anwar January 20, 2023January 20, 2023

According to a recent study from Karl Landsteiner University of Health Sciences (KL Krems), using radiomics and deep learning algorithms can quickly and accurately distinguish between glioblastoma (primary tumors) and brain metastases. The study, which was published in Metabolites, discovered that magnetic resonance-based radiological data of tumor oxygen metabolism provide a solid foundation for discrimination via…

Read More Deep Learning and Radiomics: A Game-changer for Identifying Glioblastoma and Brain Metastases
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
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
AI | Bioinformatics | Computational Models | Deep Learning | Disease Diagnosis | Health | News | Trending

Meet DeepMosaic: A Computer Program that ‘Learns’ to Identify Mosaic Mutations Causing Disease
ByDr. Tamanna Anwar January 5, 2023April 6, 2023

Scientists from the University of California San Diego School of Medicine and Rady Children’s Institute for Genomic Medicine have developed a method “DeepMosaic” for identifying mosaic mutations using deep learning. The process involves training a model to analyze large amounts of genomic data and recognize patterns associated with mosaic mutations. The researchers hope that this…

Read More Meet DeepMosaic: A Computer Program that ‘Learns’ to Identify Mosaic Mutations Causing Disease
AI | Bioinformatics | Deep Learning | Disease Diagnosis | Health | News | Trending

OpenAI’s ChatGPT: A Promising AI Tool for Early Detection of Alzheimer’s Disease
ByDr. Tamanna Anwar December 30, 2022December 31, 2022

Researchers at Drexel University’s School of Biomedical Engineering, Science, and Health Systems have found that ChatGPT, an AI-powered chatbot program, may be able to detect early signs of Alzheimer’s disease. In a study, the program analyzed conversations between individuals with Alzheimer’s disease and healthy controls and was able to accurately identify those with the disease…

Read More OpenAI’s ChatGPT: A Promising AI Tool for Early Detection of Alzheimer’s Disease
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
AI | Algorithm | Bioinformatics | Deep Learning | Machine Learning | News | Trending

AI-Powered Dementia Detection: A Digital Solution for Identifying Undiagnosed Cases
ByDr. Tamanna Anwar December 24, 2022December 24, 2022

Scientists from the Regenstrief Institute, IUPUI, Indiana University, and the University of Miami are using Artificial Intelligence to identify undiagnosed cases of dementia in primary care settings as part of the Digital Detection of Dementia (D3) study. The study aimed to improve the timely diagnosis of dementia and provide diagnostic services to those who have…

Read More AI-Powered Dementia Detection: A Digital Solution for Identifying Undiagnosed Cases
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
Bioinformatics | Computational Models | Deep Learning | Machine Learning | News | Paper Summary | Proteomics | Trending

Meet AlphaPeptDeep: a Deep Learning Framework for Predicting Peptide Properties from Sequences
ByShwetha S November 28, 2022November 28, 2022

A research team led by Professor Matthias Mann from the Max Planck Institute of Biochemistry has developed AlphaPeptDeep. AlphaPeptDeep is a Python framework built on the PyTorch deep learning library that can learn and predict peptide properties. AlphaPeptDeep additionally includes a plug-in capability that allows non-experts to develop models with just a few lines of…

Read More Meet AlphaPeptDeep: a Deep Learning Framework for Predicting Peptide Properties from Sequences
AI | Bioinformatics | Deep Learning | Neural Network | News | Paper Summary | Trending

ExpressionGAN: Generating Long Designer DNA Sequences On-Demand With Deep Learning
ByRiya Vishwakarma November 27, 2022January 20, 2024

A new deep learning method developed by a team of researchers at Chalmers can generate regulatory DNA sequences that control gene expression in a gene-specific manner. Despite significant sequence divergence from natural DNA, in vivo measurements reveal that 57% of the synthetic sequences with high expression levels outperform the expression levels of the correspondingly highly…

Read More ExpressionGAN: Generating Long Designer DNA Sequences On-Demand With Deep Learning
Bioinformatics | Cancer Research | Deep Learning | Drug Discovery | News | Paper Summary | Precision Medicine | Trending

Researchers Introduce a Deep Learning Platform ‘OrganoID’ to Track Single-organoid Dynamics for Drug Exploration
ByMahi Sharma November 16, 2022October 22, 2026

Recent research conducted by the research group of Savas Tay at the University of Chicago, Illinois, USA, introduced a deep learning platform, OrganoID to analyze and interpret the organoid models for personalized drug screening. The team has interpreted results and validated the platform using pancreatic cancer organoid images, revolutionizing biomedicine. Introduction Organoid research has…

Read More Researchers Introduce a Deep Learning Platform ‘OrganoID’ to Track Single-organoid Dynamics for Drug Exploration
Bioinformatics | Deep Learning | GWAS | News

A Novel Deep Learning Framework Identifies Gene-Gene Interactions for a Given Phenotype
ByShwetha S November 15, 2022November 15, 2022

A deep learning framework has been developed by researchers under the direction of Tianyu Cui, a Ph.D. student in the Department of Computer Science at Aalto University, to identify the gene-gene interactions underlying a given phenotype by taking into account all single nucleotide polymorphisms within a set of genes or complex interactions and calculating their…

Read More A Novel Deep Learning Framework Identifies Gene-Gene Interactions for a Given Phenotype
Algorithm | Bioinformatics | Deep Learning | Machine Learning | News | Paper Summary | Structural Biology | Trending

Meet Deep-SMOLM: A Machine Learning Algorithm for Generating 5D Images of Proteins
ByShwetha S November 8, 2022November 7, 2022

Deep-SMOLM is a deep-learning-based estimator created by Washington University in St. Louis researchers that blends machine learning, physical laws, and biological principles. At a rate ten times quicker than iterative estimators, Deep-SMOLM correctly and precisely reconstructs 5D information of simulated biological fibers and experimental amyloid fibrils from images, including highly overlapping single molecule structures. A…

Read More Meet Deep-SMOLM: A Machine Learning Algorithm for Generating 5D Images of Proteins
Bioinformatics | Biomedical Engineering | Deep Learning | News | Paper Summary | Trending

Researchers Developed Machine Learning-Based Enzyme Engineering Approach by Integrating a Logistic Regression Model
ByMahi Sharma November 7, 2022November 7, 2022

A recent study published in ACS Synthetic Biology has presented an analogous level of adaptability to enzymes. A team of researchers from Osaka University has illustrated the hypothesis to identify the amino acid residues actively involved in cofactor specificity by integrating a logistic regression model with an amino acid sequence dataset. The machine learning approach…

Read More Researchers Developed Machine Learning-Based Enzyme Engineering Approach by Integrating a Logistic Regression Model
AI | Bioinformatics | Cancer Research | Deep Learning | Health | News | Trending

Deep Learning Algorithms – the Future of Medical Imaging?
ByDr. Tamanna Anwar November 6, 2022November 6, 2022

Research presented at the 2022 World Cancer Congress shows that deep learning algorithm outperformed radiologists in detecting head and neck cancer spread. The algorithm was able to detect small areas of cancer spread that were not detected by the radiologists. This is a potentially important finding, as early detection of cancer spread can lead to…

Read More Deep Learning Algorithms – the Future of Medical Imaging?
AI | Bioinformatics | Cancer Research | Deep Learning | Health | News | Paper Summary | Trending

Researchers Introduced a Deep Learning-based Label-Free Virtual HER2 Immunohistochemical Staining of Breast Tissue
ByMahi Sharma November 1, 2022November 2, 2022

Evident with the increasing cost and laborious work of diagnosis of cancer, using the gold standard Immunohistochemical (IHC) staining of tissues. Researchers from the University of California, Los Angeles, described a label-free virtual HER2 IHC staining based on a deep learning method. Introduction Immunohistochemical staining of cancer tissues, such as the HER2 biomarker, is widely…

Read More Researchers Introduced a Deep Learning-based Label-Free Virtual HER2 Immunohistochemical Staining of Breast Tissue
AI | Bioinformatics | Cancer Research | Deep Learning | News | Paper Summary | Precision Medicine | Trending

Artificial Intelligence Strategies For Multimodal Fusion – A Path Towards Precision Oncology
ByShwetha S October 31, 2022November 9, 2022

Cancer is a significant threat worldwide. In a study published in ACS Cancer, authors Bray et al. stated that cancer may overtake cardiovascular disease as the leading cause of premature death worldwide over the course of this century. Cancer biomarkers are the biological molecules produced by the tumor in a person; this helps characterize the…

Read More Artificial Intelligence Strategies For Multimodal Fusion – A Path Towards Precision Oncology
AI | Bioinformatics | Computational Models | Deep Learning | Health | News | Paper Summary | Trending

Artificial Intelligence Accurately Predicts Patient’s Race from Medical Images – Can Lead to Unintentional Bias, Warns Scientists
ByShwetha S October 22, 2022October 22, 2022

According to the study by Prof. Judy Gichoya of Emory University, the standard deep learning models effectively predicted the patient’s race using only diagnostic images like X-rays, CT scans, and mammograms, even when the images were heavily altered, cropped, or noised. Studies have shown that AI deep learning models mimic the unconscious racial bias and…

Read More Artificial Intelligence Accurately Predicts Patient’s Race from Medical Images – Can Lead to Unintentional Bias, Warns Scientists
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’
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 | 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
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 | 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
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
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
Bioinformatics | Cancer Research | Deep Learning | Neural Network | News | Trending

Deep Learning Technology Developed by SNU Researchers Helps Predict Cancer Patient’s Survival Rate
ByDr. Tamanna Anwar August 19, 2022August 22, 2022

A research team at Seoul National University (SNU) developed deep learning technology that can more accurately predict a cancer patient’s survival rate. According to the research published today in the journal Nature Biomedical Engineering, computational pathology methods for analyzing whole-slide images (WSIs) typically do not take histopathological features from the tumor microenvironment into account. In…

Read More Deep Learning Technology Developed by SNU Researchers Helps Predict Cancer Patient’s Survival Rate
AI | Bioinformatics | Cancer Research | Deep Learning | Health | News | Paper Summary | Trending

Scientists use Multimodal Deep Learning for Pan-Cancer Integrative Histology-Genomic Analysis
ByTanveen Kaur August 14, 2022December 28, 2022

Scientists present an interpretable, loosely guided, multimodal deep learning strategy for cancer prognosis, which also investigates the use of multimodal interpretability to describe how WSI and molecular characteristics affect risk. The objective prognostic models that can be created from histology pictures have shown promise in the quickly evolving field of computational pathology. Most prognostic models,…

Read More Scientists use Multimodal Deep Learning for Pan-Cancer Integrative Histology-Genomic Analysis
AI | Bioinformatics | Deep Learning | Featured | News | Paper Summary | Structural Biology | Tools | Trending

Meta’s AI Protein Structure Prediction Model ‘ESMFold’ Predicts as Accurately and 6x Faster than AlphaFold2
BySrishti Sharma August 13, 2022October 6, 2022

Researchers at Meta AI developed an artificial intelligence (AI) model that can precisely predict entire atomic protein structures from a single sequence of a protein. The use of language model representations to replace the requirement for explicit homologous sequences distinguishes ESMFold from AlphaFold2. As a result of this simplification, ESMFold is significantly faster than the…

Read More Meta’s AI Protein Structure Prediction Model ‘ESMFold’ Predicts as Accurately and 6x Faster than AlphaFold2
Bioinformatics | Deep Learning | Machine Learning | News

Modeling New Mutational Spaces with Machine Learning
BySrishti Sharma August 12, 2022August 12, 2022

From cancer and autoimmune diseases to allergies and neurodegenerative diseases, antibody therapeutics are being used to treat human conditions. Molecular properties of antibodies, such as their high affinities, long half-lives, potent effector functions, and excellent biophysical properties (i.e., high stability and solubility), contribute significantly to the success of antibody therapeutics. Antigen-specific monoclonal antibodies (mAbs) may…

Read More Modeling New Mutational Spaces with Machine Learning
Bioinformatics | Corona Virus | COVID-19 | Deep Learning | Drug Discovery | Health | Infectious Diseases | News | Paper Summary | Structural Biology | Trending

Hierarchical Structure-based Virtual Screening Targeting SARS-CoV-2 Endoribonuclease
BySrishti Sharma August 6, 2022October 22, 2026

Since the first appearance of SARS-CoV-2, a number of in silico methods have been employed to discover possible drugs that can target the viral life cycle. Scientists from National Research Centre, Egypt, targeted Endoribonuclease, which is one of the crucial non-structural proteins since it is responsible for processing viral RNA to escape detection by the…

Read More Hierarchical Structure-based Virtual Screening Targeting SARS-CoV-2 Endoribonuclease
Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Trending

A Deep Unsupervised Language Model ‘ProtGPT2’ for Protein Design
BySrishti Sharma August 4, 2022August 4, 2022

Scientists from the University of Bayreuth, Germany, introduced ProtGPT2, a language model for protein design trained on the protein space that generates de novo protein sequences following the principles of natural ones. ProtGPT2-sequences predicted using AlphaFold result in well-folded, non-idealized structures. ProtGPT2 generates sequences in a fraction of seconds and has open source access. Novel…

Read More A Deep Unsupervised Language Model ‘ProtGPT2’ for Protein Design
AI | Algorithm | Bioinformatics | Cancer Research | Computational Models | Deep Learning | Health | Neural Network | News | Paper Summary | Trending

Scientists Develop Digital Pathology Models without Human Intervention by Integrating Clinical Healthcare Data with AI
ByTanveen Kaur July 29, 2022November 11, 2022

Scientists unleash the potential of digital pathology data by training computer-aided diagnosis models and making use of convolutional neural networks without human annotations. The cancer diagnostics model developed in the study for empowering digital pathology limits the human effort to a minimum. Deep learning algorithms’ improved performance and the digitization of healthcare operations are opening…

Read More Scientists Develop Digital Pathology Models without Human Intervention by Integrating Clinical Healthcare Data with AI
Bioinformatics | Cancer Research | Deep Learning | News | Transcriptomics | Trending

SpaceFlow – A Deep Learning Framework to Integrate Spatiotemporal Information in Analyzing Spatial Transcriptomic Data
ByTanveen Kaur July 19, 2022November 11, 2022

Scientists from the University of California Irvine introduced SpaceFlow, which, by the utilization of spatially regularized deep graph networks, combines expression similarity with geographical information to provide spatially-consistent low-dimensional embeddings. Applications of SpaceFlow show evolving lineage in data on heart development and tumor-immune interactions in data on human breast cancer. The simultaneous integration of cell…

Read More SpaceFlow – A Deep Learning Framework to Integrate Spatiotemporal Information in Analyzing Spatial Transcriptomic Data
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A Geometric Deep-Learning Model ‘EquiBind’ the Fastest Computational Molecular Docking Model
ByTanveen Kaur July 17, 2022October 22, 2026

MIT researchers have developed a geometric deep-learning model, EquiBind, which is 1,200 times faster than one of the fastest computational molecular docking models currently in use, QuickVina2-W, for effective binding of drug-like substances to proteins. One of the main challenges in drug discovery is to predict the binding properties of a drug-like chemical to a…

Read More A Geometric Deep-Learning Model ‘EquiBind’ the Fastest Computational Molecular Docking Model
Bioinformatics | Deep Learning | Neural Network | News | Structural Biology | Trending

Identification of Physiological and Adventitious Metal-Binding Sites in Protein 3D Structures Using a Deep Neural Network-Based Classifier
ByTanveen Kaur July 9, 2022November 9, 2022

Scientists used a deep learning approach to create a ‘Deep Neural Network Classifier’ that can distinguish between physiologic and accidental zinc-binding sites in the 3D structure of metalloproteins. The Protein Data Bank contains at least one metal ion in 38% of protein structures. Not all of these metal sites, nevertheless, have biological significance. Protein-metal complexes…

Read More Identification of Physiological and Adventitious Metal-Binding Sites in Protein 3D Structures Using a Deep Neural Network-Based Classifier
AI | Bioinformatics | Deep Learning | Health | Infectious Diseases | News | Trending

AI-Powered Innovative Bacterial Colony Detection System Using a Thin-Film Transistor (TFT) Array – A Technology Often Seen in Mobile Phone Displays
ByDr. Tamanna Anwar July 7, 2022July 7, 2022

A research team led by Professor Aydogan Ozcan from the Electrical and Computer Engineering Department at the University of California, Los Angeles (UCLA) and colleagues have developed an artificial intelligence (AI) powered innovative bacterial colony detection system using a thin-film transistor (TFT) array, which is a widely used technology in mobile phones and other displays….

Read More AI-Powered Innovative Bacterial Colony Detection System Using a Thin-Film Transistor (TFT) Array – A Technology Often Seen in Mobile Phone Displays
AI | Algorithm | Bioinformatics | Cancer Research | Deep Learning | Health | Neural Network | News | Tools | Trending

TranSalNet – AI System that Simulates Human Vision Holds Potential Application in Cancer Detection
ByDr. Tamanna Anwar July 5, 2022December 28, 2022

Scientists at Cardiff University have developed a state-of-the-art artificial intelligence (AI) system, ‘TranSalNet,’ which precisely anticipates the regions of an image where a person is most likely to gaze. The researchers claim that the unique method more accurately simulates human vision than any previous system based on human brain mechanics and its ability to discriminate…

Read More TranSalNet – AI System that Simulates Human Vision Holds Potential Application in Cancer Detection
AI | Bioinformatics | Cancer Research | Deep Learning | News | Paper Summary | Trending

Disease Prognosis Using Deep Learning and H&E Images – Emerging Tool for Clinical Trial Optimization
ByTanveen Kaur June 17, 2022September 2, 2022

Scientists used hematoxylin and eosin (H&E) images with a deep learning approach to predict disease outcomes, an emerging technique for the improvement of clinical trials via computational methodology. For treatment choices and disease outcome monitoring, it is highly clinically relevant to understand the variables that affect a cancer patient’s prognosis. The use of whole slide images…

Read More Disease Prognosis Using Deep Learning and H&E Images – Emerging Tool for Clinical Trial Optimization
AI | Bioinformatics | Deep Learning | News | RNA-Seq | Trending

Scientists Employ RNA Velocity and Deep Learning to Study Gene Regulation Dynamics During Cell Cycle
ByTanveen Kaur May 27, 2022November 9, 2022

Scientists have developed DeepCycle, a deep learning approach combined with RNA velocity to reveal cell cycle gene regulation. This methodology is particularly appropriate to study the interplay of the cell cycle with pluripotency and cell reprogramming. The method could lead to the discovery of cell-cycle dysregulated mechanisms in malignancies, as well as prospective therapeutic targets. Even…

Read More Scientists Employ RNA Velocity and Deep Learning to Study Gene Regulation Dynamics During Cell Cycle

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Deep Learning

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