Deep Learning

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Unveiling the Power of Deep Learning: A Comprehensive Benchmark of Tertiary RNA Structure Prediction Methods
ByDeotima Chakraborty February 12, 2024October 22, 2026

Before understanding RNA biology, one must grasp the three-dimensional structure of RNA. Because experimental procedures require a lot of labor and money, computer approaches have emerged. With the use of machine learning and physics-based concepts, these techniques can quickly anticipate RNA structures. On the other hand, their accuracy is still not as high as that…

Read More Unveiling the Power of Deep Learning: A Comprehensive Benchmark of Tertiary RNA Structure Prediction Methods
AI | Bioinformatics | Drug Discovery | LLM | News | Trending

Unleashing nanoBERT: Revolutionizing Nanobody Therapeutics with Deep Learning
ByDr. Tamanna Anwar February 9, 2024October 22, 2026

Scientists from the University of Southern Denmark, NaturalAntibody and Alector Therapeutics unveil nanoBERT, a nanobody-specific transformer designed to predict amino acids in specific positions within query sequences. NanoBERT outperforms human-based language models and ESM-2, demonstrating the benefits of domain-specific language modeling. Fine-tuning on thermostability datasets shows promise for engineering therapeutic nanobodies. Nanobodies, also known as…

Read More Unleashing nanoBERT: Revolutionizing Nanobody Therapeutics with Deep Learning
AI | Bioinformatics | Database | Deep Learning | News | Structural Biology | Trending

Revolutionize RNA Structure Prediction with RNA3DB: The Pinnacle Dataset for Training Deep Learning Models
ByDr. Tamanna Anwar February 6, 2024October 22, 2026

Harvard University researchers introduce RNA3DB, a dataset crafted from the Protein Data Bank (PDB), addressing challenges in RNA structure prediction. In response to limitations in existing literature and recent findings in CASP15, RNA3DB offers a non-redundant dataset for training and benchmarking deep learning models. With the success of deep learning in protein structure prediction, there…

Read More Revolutionize RNA Structure Prediction with RNA3DB: The Pinnacle Dataset for Training Deep Learning Models
AI | Bioinformatics | Deep Learning | Gene Expression | Genomics | News | Paper Summary | Trending

Unlocking the Enhancer Code: Deep Learning’s Role in Designing Cell-specific Genetic Switches
ByAnchal Negi February 4, 2024October 22, 2026

Transcriptional enhancers control the spatiotemporal activation of the target genes they regulate by serving as docking stations for various transcription factor combinations. It has been a long goal to Decipher the regulatory logic of an enhancer and comprehend the specifics of how spatiotemporal gene expression is encoded in an enhancer sequence. Researchers from VIB Center…

Read More Unlocking the Enhancer Code: Deep Learning’s Role in Designing Cell-specific Genetic Switches
AI | Bioinformatics | Deep Learning | Drug Discovery | LLM | News | Paper Summary | Structural Biology | Trending

Meet Lingo3DMol: A Pocket-based 3D Molecule Generation Method Leveraging Language Models and Geometric Deep Learning
ByAnchal Negi January 27, 2024October 22, 2026

The drug development process involves a winding trail across the enormous chemical wilderness, looking for compounds that interact ideally with their target proteins. Traditional approaches, while successful, frequently stumble in the dark, unable to capture the delicate 3D pattern of particles and their interactions. But do not worry; scientists from Beijing StoneWise Technology Co Ltd, …

Read More Meet Lingo3DMol: A Pocket-based 3D Molecule Generation Method Leveraging Language Models and Geometric Deep Learning
AI | Bioinformatics | Deep Learning | Drug Discovery | LLM | News | Tools | Trending

Language Models Paired with Geometric Deep Learning Revolutionize Genome-scale Protein Binding Site Annotation
ByDeotima Chakraborty January 17, 2024October 22, 2026

Protein structures depend on nucleic acids and tiny ligands to establish binding sites. Accurate identification of these locations is necessary due to the exponential increase of protein sequence databases. However, the current approaches do not thoroughly address the geometry of protein structures and limit genome-scale applications by relying on costly multiple sequence alignments or experimental…

Read More Language Models Paired with Geometric Deep Learning Revolutionize Genome-scale Protein Binding Site Annotation
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Trending

High-throughput ADMET Properties Prediction Made Easy with ADMET-AI: A New Platform for Large-scale Chemical Libraries Evaluation
ByAnchal Negi January 13, 2024October 22, 2026

A vital step in drug discovery is accurately evaluating potential drug candidates’ Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET). Traditionally, this process has been time-consuming, expensive, and even limited to small compound libraries, making it difficult to test larger libraries. Recently, a group of researchers developed ADMET-AI, a simple, fast, and accurate platform for ADMET…

Read More High-throughput ADMET Properties Prediction Made Easy with ADMET-AI: A New Platform for Large-scale Chemical Libraries Evaluation
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Tools | Trending

Meet LigandMPNN: A Deep Learning Model Redefining Protein Design with Precision for Small Molecules, Nucleotides, and Metals
BySonal Keni January 2, 2024January 2, 2024

Protein design is an upcoming niche with important implications for many fields in the realms of healthcare, genetic engineering, and drug creation, among others. However, current methods for sequence design have many disadvantages, including a lack of appropriate accuracy and efficiency. A new model, LigandMPNN, seeks to change this. The design of protein sequences is…

Read More Meet LigandMPNN: A Deep Learning Model Redefining Protein Design with Precision for Small Molecules, Nucleotides, and Metals
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Paper Summary | Proteomics | Structural Biology | Trending

Decoding the Protein-Ligand Enigma: A Deep Dive into Deep Learning Approaches for Binding Affinity Prediction
ByDeotima Chakraborty November 30, 2023November 30, 2023

Researchers from the University of Edinburgh, UK, explore the impact of ligand and protein encodings on binding affinities prediction for different data sets, a crucial aspect of drug development and discovery. Sequence-based deep learning, convolutional neural network-based encodings, and graph neural network-based encodings were used to investigate protein roles. Graph-neural networks were used to construct…

Read More Decoding the Protein-Ligand Enigma: A Deep Dive into Deep Learning Approaches for Binding Affinity Prediction
AI | Big Data | Bioinformatics | Genomics | LLM | News | OMICS | Paper Summary | Trending

Genome LLMs: Revolutionizing Genomics with Transformer-based Large Language Models
BySwasti Tyagi November 29, 2023November 29, 2023

Deep learning techniques have had a significant influence on genomics and the sequencing techniques employed in the field due to the exponential advancements in artificial intelligence (AI) and machine learning (ML) during the past ten years. The review article by a team led by researchers from the University of Toronto elucidates the advantages and drawbacks…

Read More Genome LLMs: Revolutionizing Genomics with Transformer-based Large Language Models
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DeepSA: A Cutting-edge Chemical Language Model for Compound Synthesis Accessibility Prediction
BySonal Keni November 10, 2023November 28, 2023

As computationally generated molecules become more popular in the fields of drug development and biotechnology, ease of synthesis becomes a common problem. Often, the molecules generated by machine learning models may be challenging to synthesize and may require many steps, making it too expensive for production. A new deep learning model DeepSA, developed by researchers…

Read More DeepSA: A Cutting-edge Chemical Language Model for Compound Synthesis Accessibility Prediction
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The AlphaFold Revolution Continues: Unraveling the Next-Gen Advancements
BySonal Keni November 6, 2023October 22, 2026

The introduction of AlphaFold 2 was a groundbreaking breakthrough in the field of predicting protein structures and interactions. Google’s DeepMind, was the driving force behind this tool, which used deep learning methods in order to successfully predict the structures of various proteins. Described by many experts in the field as one of the most transformational…

Read More The AlphaFold Revolution Continues: Unraveling the Next-Gen Advancements
AI | Bioinformatics | Computational Models | Deep Learning | Neural Network | News | Paper Summary | Trending

Deep Learning Meets Clinical Microbiology: Unveiling DeepColony for Automated Culture Plates Interpretation
BySonal Keni November 4, 2023November 23, 2023

The introduction of Full Laboratory Automations has served to revolutionize the workflows of labs worldwide, helping with the automation of routine tasks and the capacity for digital analysis of the results. However, a significant limitation is the inability to identify and interpret bacterial cultures, a task that is considered essential in the field of microbiology…

Read More Deep Learning Meets Clinical Microbiology: Unveiling DeepColony for Automated Culture Plates Interpretation
Bioinformatics | Deep Learning | News | Paper Summary | Tools | Trending

Meet BTR: A Deep Learning Powered Bioinformatics Tool Recommendation System Revolutionizing Workflow Construction
BySonal Keni October 26, 2023October 26, 2023

With the rise in popularity of the field of bioinformatics in recent years, researchers have created multiple computational tools that help streamline and optimize the research process. However, while the use of such tools may seem intuitive to an experienced researcher, newer researchers and researchers who don’t have as much experience with bioinformatics workflows may…

Read More Meet BTR: A Deep Learning Powered Bioinformatics Tool Recommendation System Revolutionizing Workflow Construction
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Paper Summary

Deep Learning Unveils Antimalarial Drug’s Potential to Combat Osteoporosis
BySonal Keni October 24, 2023January 10, 2024

Scientists at Peking University School and Hospital for Stomatology, China, have used deep learning to identify dihydroartemisinin (DHA), an antimalarial drug, as a potential treatment for osteoporosis. DHA was found to maintain the stemness of mesenchymal stem cells (MSCs), which are important for bone formation. In mice, DHA treatment was able to reverse osteoporosis-related bone…

Read More Deep Learning Unveils Antimalarial Drug’s Potential to Combat Osteoporosis
Bioinformatics | Cell | Deep Learning | News | NGS | Paper Summary | RNA-Seq | Tools | Trending

Decoding Cellular Interactions with DeepCCI: A Deep Learning Approach to Analyze Single-cell RNA Sequencing Data
ByPrachi Khare October 20, 2023October 21, 2023

Cell-cell interactions (CCIs) are pivotal in various biological functions, including cellular differentiation, tissue maintenance, and immune reactions. As single-cell RNA sequencing (scRNA-seq) techniques advance, the need to discern CCIs from the growing pool of data becomes crucial. A groundbreaking technique, “DeepCCI,” developed by researchers from the Harbin Institute of Technology, China, uses scRNA-seq data to…

Read More Decoding Cellular Interactions with DeepCCI: A Deep Learning Approach to Analyze Single-cell RNA Sequencing Data
AI | Bioinformatics | Cancer Research | Neural Network | News | NGS | Paper Summary | Trending

Fast-tracking CNS Tumor Diagnosis: New AI System ‘Sturgeon’ Accurately Diagnoses Brain Tumors in Minutes
BySonal Keni October 17, 2023October 17, 2023

Tumors that affect the central nervous system are among the most fatal kinds of cancer, especially in pediatric cases. Surgical removal of the tumor is usually the prescribed course of action, made harder by the fact that the surgeons performing the procedure will not be able to determine the kind of tumor they’re dealing with…

Read More Fast-tracking CNS Tumor Diagnosis: New AI System ‘Sturgeon’ Accurately Diagnoses Brain Tumors in Minutes
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Paper Summary | Structural Biology | Trending

Pharmacophore-Guided Deep Learning: A New Paradigm for Generating Bioactive Molecules in Drug Discovery
BySwasti Tyagi October 15, 2023October 15, 2023

One of the biggest challenges to drug discovery is designing molecules that express desired biological activity, also referred to as bioactivity. This is of great importance when intending to use the drug for treating diseases that have not been thoroughly researched. To tackle this, researchers from Central South University, China, developed PGMG, which stands for…

Read More Pharmacophore-Guided Deep Learning: A New Paradigm for Generating Bioactive Molecules in Drug Discovery
AI | Bioinformatics | Deep Learning | Neural Network | News | Paper Summary | Proteomics | Trending

A New Deep Neural Networks-Based Method Predicts Protein Abundance Based on Amino Acid Sequence
BySonal Keni October 12, 2023November 24, 2023

With the potential to have significant impacts on various fields, like therapeutics and agritech, protein engineering has recently been a subject that has incited much intrigue within the scientific community. However, despite this, many factors that govern the synthesis and regulation of proteins aren’t well-known. The intricate relationships that influence the various interactions proteins have…

Read More A New Deep Neural Networks-Based Method Predicts Protein Abundance Based on Amino Acid Sequence
AI | Bioinformatics | Deep Learning | Disease Diagnosis | Drug Discovery | News | Paper Summary | Tools | Trending

MitoSpace: A Novel Mitochondrial Phenotypic Atlas for Drug Discovery and Diagnostics
BySwasti Tyagi September 27, 2023October 22, 2026

A collaborative effort between the Departments of Pharmacology, Chemistry, and Biochemistry at the University of California, San Diego, led to the development of MitoSpace, a self-supervised deep learning model. It can be considered an ‘atlas’ to map various phenotypic characteristics of the mitochondria’s reactions and responses to different drugs. It is a high-content image-based screening…

Read More MitoSpace: A Novel Mitochondrial Phenotypic Atlas for Drug Discovery and Diagnostics
AI | Bioinformatics | Computational Models | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Trending

Meet DRfold: A Novel Method to Predict RNA Tertiary Structures with Unprecedented Accuracy
ByPrachi Khare September 21, 2023October 22, 2026

RNAs are essential components of physiological activities, however, accurately modeling their structures has long posed a challenge due to their complex structures. The National University of Singapore researchers introduced DRfold, an innovative technique to predict RNA complex 3D structures. By simultaneously learning local frame rotations and geometric constraints from experimentally solved RNA structures, DRfold addresses…

Read More Meet DRfold: A Novel Method to Predict RNA Tertiary Structures with Unprecedented Accuracy
AI | Big Data | Bioinformatics | Data Science | Deep Learning | Genomics | Health | Neural Network | News | Trending

Large Language Models Offering Solutions to Tackle Biological Complexity
ByNeegar Naushaba Iqbal September 6, 2023January 1, 2024

Large Language Models (LLMs) have emerged as dynamic tools with the ability to transform the landscape of biological research in a world driven by data and technology. These advanced AI models, including well-known names like BERT and GPT, are not confined to linguistics but have found their way into the complex realm of biology. In…

Read More Large Language Models Offering Solutions to Tackle Biological Complexity
AI | Bioinformatics | Deep Learning | News | Paper Summary | RNA-Seq | Tools | Transcriptomics | Trending

Stanford’s GEARS: An Innovative Approach to Predicting Transcriptional Outcomes of Multigene Perturbation
ByNeegar Naushaba Iqbal August 23, 2023August 23, 2023

Understanding cellular responses to genetic changes holds vital importance in various biomedical contexts, such as uncovering cancer-related genetic interactions and advancing regenerative medicine. However, the vast number of potential multigene alterations poses a challenge for practical experimentation. In this regard, a novel method called the graph-enhanced gene activation and repression simulator (GEARS) has been introduced…

Read More Stanford’s GEARS: An Innovative Approach to Predicting Transcriptional Outcomes of Multigene Perturbation
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
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 | 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
AI | Bioinformatics | Drug Discovery | Facts | Machine Learning | Trending

The Future of Medicine is Here: Top Tech Transforming Drug Discovery
ByAnjali Soni May 24, 2022October 22, 2026

The advent of technological advances such as artificial intelligence (AI), machine learning (ML), automation, robotics, etc., has accelerated the pace of drug discovery as well as the constancy maintained by the automated procedure reduces human errors and provides improved data quality. The goal of drug discovery and development is to bring new medicines to patients…

Read More The Future of Medicine is Here: Top Tech Transforming Drug Discovery
AI | Bioinformatics | Cancer Research | Deep Learning | Machine Learning | News | Paper Summary | Tools | Trending

‘CancerVar’ – A New Machine Learning Empowered Tool to Interpret Somatic Variants in Cancer
ByTanveen Kaur May 18, 2022November 9, 2022

CancerVar leverages machine learning frameworks to evaluate the potential relevance of somatic cancer mutations in terms of cancer diagnosis, prognosis, and targetability, in addition to simply discovering them. Researchers at Children’s Hospital of Philadelphia (CHOP) developed CancerVar, a novel machine learning empowered tool to interpret somatic variants in cancer. CancerVar can be accessed either as…

Read More ‘CancerVar’ – A New Machine Learning Empowered Tool to Interpret Somatic Variants in Cancer
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‘DeepRank’ – A Deep Learning Framework for Data Mining Protein-Protein Interfaces Using 3D Convolutional Neural Networks
ByTanveen Kaur May 16, 2022November 9, 2022

Scientists formulate a deep learning framework, DeepRank, for the data mining of 3D protein-protein interfaces. They demonstrated the efficiency and readiness of DeepRank on two unique difficulties in structural biology. 3D structures of protein complexes give essential data to decipher biological processes at the molecular scale. The huge measure of experimentally and computationally resolved protein-protein…

Read More ‘DeepRank’ – A Deep Learning Framework for Data Mining Protein-Protein Interfaces Using 3D Convolutional Neural Networks
AI | Bioinformatics | Computational Models | Covid-19 News | Deep Learning | Machine Learning | Neural Network | News | Paper Summary | Structural Biology | Trending

A Novel Parallel Graph Neural Networks Based Method for Decoding Protein-Ligand Interactions
ByTanveen Kaur May 14, 2022November 9, 2022

A deep learning-based method for predicting the biophysical and biochemical features of protein-ligand complexes developed by researchers could help discover new drug candidates. Scientists formulate novel parallel graph neural networks for decoding protein-ligand interactions. This methodology can serve as an interpretable and explainable artificial intelligence (AI) tool for predicted activity, potency, and biophysical properties of…

Read More A Novel Parallel Graph Neural Networks Based Method for Decoding Protein-Ligand Interactions
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Top 10 Applications of Artificial Intelligence in Healthcare
ByAnjali Soni May 11, 2022December 28, 2022

Top 10 Applications of Artificial Intelligence in Healthcare in 2022 and Beyond The healthcare industry has always been one of the leaders in using technology to make lives better and more efficient. Artificial intelligence (AI) in healthcare has started to enter the market, but it’s not just used as an additional tool — it’s transforming…

Read More Top 10 Applications of Artificial Intelligence in Healthcare
AI | Bioinformatics | Cancer Research | Deep Learning | Machine Learning | News | Paper Summary

Deep Neural Network Based 3D Reconstruction of Cellular Images to Track Real-Time Response of Tissues to Cancer Therapy
ByTanveen Kaur May 8, 2022November 9, 2022

Microscopic imagers may be used in oncology to track and observe cell motions and dynamics, indicating tissues’ real-time response to therapy. Scientists from the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, reconstruct cellular images in 3D from microfabricated imagers using fully-adaptive deep neural networks. This research is the first work that…

Read More Deep Neural Network Based 3D Reconstruction of Cellular Images to Track Real-Time Response of Tissues to Cancer Therapy
Bioinformatics | Deep Learning | News | Paper Summary | Tools | Trending

Scientists Develop a Deep Learning Model ‘CAESAR’ to Connect High-Resolution 3-Dimensional Chromatin Organization With Epigenomics
ByDr. Tamanna Anwar April 22, 2022June 18, 2022

Researchers from the University of Michigan, USA, developed a deep learning model, CAESAR (Chromosomal structure And EpigenomicS AnalyzeR), to predict nucleosome-resolution 3D chromatin contact maps from existing epigenomic features and lower-resolution Hi-C contact maps. The imputed high-resolution contact maps could help in target finding, hypotheses generation, and other downstream analyses. The resolution of chromatin conformation…

Read More Scientists Develop a Deep Learning Model ‘CAESAR’ to Connect High-Resolution 3-Dimensional Chromatin Organization With Epigenomics
AI | Bioinformatics | Cancer Research | Deep Learning | Machine Learning | News | Paper Summary | Trending

Scientists Analyze the Promising Role of Prostate Cancer’s New Molecular Biomarkers: From Coding and Non-Coding Genes to Artificial Intelligence Techniques
ByTanveen Kaur April 20, 2022November 9, 2022

The scientists from Unidad de Investigación Biomédica en Cáncer, México, looked at numerous facets of prostate cancer, including new molecular markers linked to diagnosis, prognosis, therapy prediction, and how bioinformatics tools like machine learning and deep learning can help in the clinic. The findings are expected to improve prostate cancer patient clinical care by applying…

Read More Scientists Analyze the Promising Role of Prostate Cancer’s New Molecular Biomarkers: From Coding and Non-Coding Genes to Artificial Intelligence Techniques
Bioinformatics | Computational Models | Data Science | Deep Learning | Machine Learning | News | Paper Summary | Proteomics

Protein Function and Properties Characterization Using Language Models
ByTanveen Kaur April 17, 2022October 22, 2026

In recent years, deep learning algorithms have shown promise in identifying protein function and extracting complex sequence-structure-function correlations. Scientists from Middle East Technical University and Karadeniz Technical University present a benchmarking study that compares the results and benefits of various deep learning algorithms in various protein prediction tasks. The data-centric approaches have been utilized for…

Read More Protein Function and Properties Characterization Using Language Models
Algorithm | Bioinformatics | Cell | Computational Models | Deep Learning | Machine Learning | News | OMICS | Paper Summary | Tools

DGCyTOF: Deep Learning with Graphic Cluster Visualisation Model for Predicting Cell Types from Single-Cell Mass Cytometry Data
ByTanveen Kaur April 16, 2022November 9, 2022

Researchers from The Ohio State University utilized deep-learning classification and hierarchical stable-clustering approaches to predict cell types from single-cell mass cytometry data. The DGCyTOF approach could facilitate the analysis of single-cell RNASeq data and other omics data. Single-cell mass cytometry, also called cytometry by time of flight (CyTOF), is a powerful high-throughput technology that permits…

Read More DGCyTOF: Deep Learning with Graphic Cluster Visualisation Model for Predicting Cell Types from Single-Cell Mass Cytometry Data
AI | Bioinformatics | Computational Models | Data Science | Deep Learning | Drug Discovery | Featured | News | Paper Summary | Structural Biology | Tools | Trending

A Deep Learning Model ‘AF2complex’ for Predicting Protein Complex Structures and Protein-Protein Interactions
ByDr. Tamanna Anwar April 2, 2022October 22, 2026

Scientists from the Center for the Study of Systems Biology, Atlanta, in collaboration with the Georgia Institute of Technology, Atlanta, and Oak Ridge National Laboratory, Oak Ridge, USA, have introduced a new method, ‘AF2complex’, in which AlphaFold2 (AF2) can be used to predict protein complex structure and protein-protein interactions. It is expected to provide significant…

Read More A Deep Learning Model ‘AF2complex’ for Predicting Protein Complex Structures and Protein-Protein Interactions
AI | Bioinformatics | Corona Virus | COVID-19 | Covid-19 News | Data Science | Deep Learning | Featured | Machine Learning | Paper Summary | Trending

Scientists Developed a Hybrid Machine Learning/Deep Learning Based Covid-19 Severity Prediction Model to Support Clinical Decision Making
ByTanveen Kaur March 23, 2022November 9, 2022

Scientists from Fondazione Poliambulanza Istituto Ospedaliero, Italy, developed a hybrid machine learning/deep learning model to classify patients in two outcome categories, non-ICU, and ICU. With the likelihood score belonging to an outcome class and case-based SHAP interpretation of feature importance, the model intends to give clinical decision support to medical physicians. The scientists devised a…

Read More Scientists Developed a Hybrid Machine Learning/Deep Learning Based Covid-19 Severity Prediction Model to Support Clinical Decision Making

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Deep Learning

Deep Learning Unveils Antimalarial Drug’s Potential to Combat Osteoporosis

A Geometric Deep-Learning Model ‘EquiBind’ the Fastest Computational Molecular Docking Model

Deep Neural Network Based 3D Reconstruction of Cellular Images to Track Real-Time Response of Tissues to Cancer Therapy

Protein Function and Properties Characterization Using Language Models

DGCyTOF: Deep Learning with Graphic Cluster Visualisation Model for Predicting Cell Types from Single-Cell Mass Cytometry Data

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