AI

How artificial intelligence is changing biology and medicine, from protein structure prediction to AI-driven drug discovery and genomics.

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AI vs. Superbugs: A New Generative AI Model ‘SyntheMol’ Designs Powerful Antibiotics to Fight Resistant Bacteria
ByDeotima Chakraborty March 25, 2024October 22, 2026
AI is being used to find novel antibiotics for bacteria resistant to pandemics; however, the currently used techniques have serious drawbacks. While generative models design molecules—which are difficult to synthesize—property prediction models, which assess molecules individually, have difficulty scaling to enormous chemical spaces. The generative model SyntheMol, which creates readily synthesizable chemicals from a chemical…
Read More AI vs. Superbugs: A New Generative AI Model ‘SyntheMol’ Designs Powerful Antibiotics to Fight Resistant Bacteria
AI | Bioinformatics | Covid-19 News | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Trending
Creating Antibodies from Scratch: Scientists Design Single-Domain Antibodies with Atomic Precision Using AI
ByDeotima Chakraborty March 21, 2024October 22, 2026
The inability to logically design new antibodies that bind a particular epitope on a target persists despite the crucial role that antibodies play in contemporary medicine. Instead, time-consuming animal immunization procedures or library screening techniques are currently used in antibody development. Here, scientists from the University of Washington show that user-specified epitopes can be bound…
Read More Creating Antibodies from Scratch: Scientists Design Single-Domain Antibodies with Atomic Precision Using AI
AI | Bioinformatics | LLM | News | Paper Summary | Proteomics | Tools | Trending
Unveiling PROTLLM: The Next Generation Cross-Modal Large Language Model for Protein-Centric and Language Tasks
ByDeotima Chakraborty March 18, 2024October 22, 2026
PROTLLM is a versatile crossmodal large language model (LLM) proposed by Beijing Institute of Technology researchers designed for protein-centric and protein-language tasks. It can handle complicated inputs with natural language text mixed with an arbitrary number of proteins thanks to its dynamic protein mounting technique. By creating a specialized protein vocabulary, the proteins-word language modeling approach…
Read More Unveiling PROTLLM: The Next Generation Cross-Modal Large Language Model for Protein-Centric and Language Tasks
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Tools | Trending
Basecamp Research Introduces BaseFold: A New Deep Learning Approach to Protein Structure Prediction
ByDeotima Chakraborty March 17, 2024October 22, 2026
Scaling laws predict the presence of over a trillion species on our planet. However, only a small fraction of them have been studied. Deep learning models applied for work in life sciences generally depend on the size and quality of training or reference datasets. The study suggests a data-centric strategy to improve deep learning models…
Read More Basecamp Research Introduces BaseFold: A New Deep Learning Approach to Protein Structure Prediction
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Trending
Exploring the Boundless Frontiers of Biomolecular Modeling and Design with RoseTTAFold All-Atom
ByDeotima Chakraborty March 14, 2024October 22, 2026
Models like AlphaFold2 (AF2) and RoseTTAFold, a modified structural biology tool, have not been able to replicate well the interactions or covalent changes with tiny molecules that are essential to biological activity. Here, researchers from the University of Washington describe RoseTTAFold All-Atom (RFAA), a deep network that, given the sequences of the polymers and the…
Read More Exploring the Boundless Frontiers of Biomolecular Modeling and Design with RoseTTAFold All-Atom
AI | Bioinformatics | Cancer Research | News | Paper Summary | Trending
Prostate Cancer: Beyond One Disease? AI Uncovers Hidden Diversity
ByAnchal Negi March 13, 2024October 22, 2026
Prostate cancer remains a significant health threat for men globally. The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to proliferate and ultimately invade and metastasize to other tissues rapidly. New research sheds light on how a prostate cancer diagnosis can…
Read More Prostate Cancer: Beyond One Disease? AI Uncovers Hidden Diversity
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Decoding Genes and Cells with GenePT: A Simple Yet Powerful Foundation Model Leveraging ChatGPT
ByDeotima Chakraborty March 11, 2024October 22, 2026
Large-scale gene expression data is used by Geneformer and scGPT models to build fundamental single-cell biology models. These models implicitly learn gene and cellular activities from millions of cell expression profiles, necessitating labor-intensive training and considerable data curation. Here, researchers from Stanford University use gene embeddings from the literature leveraging ChatGPT to investigate a much…
Read More Decoding Genes and Cells with GenePT: A Simple Yet Powerful Foundation Model Leveraging ChatGPT
AI | Bioinformatics | LLM | News | Paper Summary | Structural Biology | Trending
Unveiling the Potential of RiNALMo: Advancing RNA Structure Prediction with General-Purpose RNA Language Models
ByDeotima Chakraborty March 8, 2024October 22, 2026
Numerous fundamental functions of ribonucleic acid (RNA) are involved in basic biological processes. It is imperative that we deepen our comprehension of the structures and activities of RNA, as it has emerged as an intriguing target for pharmaceuticals in recent times. Sequencing technologies have yielded vast amounts of unlabeled RNA data throughout the years, concealing…
Read More Unveiling the Potential of RiNALMo: Advancing RNA Structure Prediction with General-Purpose RNA Language Models
AI | Bioinformatics | Chemoinformatics | Computational Models | Drug Discovery | News | Paper Summary | Structural Biology | Trending
Microsoft Reveals ViSNet: A Cutting-Edge Framework for Molecular Property Prediction and Simulating Molecular Dynamics
ByAnchal Negi March 7, 2024October 22, 2026
Molecular geometry modeling, which involves building models that show the spatial arrangement of atoms in a molecule, usually helps with this understanding. The field of molecular modeling has been transformed by geometric deep learning. However, due to molecules’ inherent 3D shape and the intricate interactions between their constituent atoms, standard deep learning algorithms need help…
Read More Microsoft Reveals ViSNet: A Cutting-Edge Framework for Molecular Property Prediction and Simulating Molecular Dynamics
AI | Bioinformatics | Computational Models | Neural Network | News | Paper Summary | Structural Biology | Trending
Revolutionizing Protein-Nucleic Acid Binding Prediction with PNAbind: A Graph Neural Network Approach
ByDeotima Chakraborty March 6, 2024October 22, 2026
The geometric characteristics of protein-nucleic acid complexes, which are explored using structural models, are crucial for proteins to recognize and bind nucleic acids. However, these features are limited when compared to unbound proteins. PNAbind is a deep learning method that the University of Southern California researchers have developed for predicting protein-nucleic acid (protein-NA) binding based…
Read More Revolutionizing Protein-Nucleic Acid Binding Prediction with PNAbind: A Graph Neural Network Approach
AI | Bioinformatics | LLM | News | Paper Summary | Proteomics | Tools | Trending
ProLLaMA: A Multi-Tasking Protein Language Model Ushering in a New Era in Protein Science
ByAnchal Negi March 5, 2024October 22, 2026
The versatile workhorses of our cells, proteins, are essential to many biological processes. Numerous scientific endeavors, such as medication research and the creation of biomaterials, depend on our ability to comprehend their structure and function. Protein research has always been a laborious and time-consuming process. However, protein language models (PLMs) are revolutionizing this field by…
Read More ProLLaMA: A Multi-Tasking Protein Language Model Ushering in a New Era in Protein Science
AI | Bioinformatics | LLM | News | Paper Summary | Proteomics | Tools | Trending
Unveiling PTM-Mamba: Revolutionizing Proteomics with PTM-Aware Protein Language Model
ByDeotima Chakraborty March 5, 2024October 22, 2026
In living organisms, different types of proteins are essential for a variety of critical processes. The structural and functional diversity of many protein types is greatly influenced by post-translational modifications (PTMs), which allow cells to respond to changes in their environment and control intricate biological processes. Though they do not take into consideration the effects…
Read More Unveiling PTM-Mamba: Revolutionizing Proteomics with PTM-Aware Protein Language Model
AI | Bioinformatics | Gene Expression | Genomics | News | Paper Summary | Sequencing | Trending
Unraveling Genetic Mysteries with Proformer: A Hybrid Macaron Transformer Model
ByDeotima Chakraborty March 4, 2024October 22, 2026
The ability to comprehensively decode the cis-regulatory logic that controls the expression values is made possible by the revolutionary high-throughput measurement of the cis-regulatory activity of millions of randomly produced promoters. Researchers from the University of Minnesota developed an end-to-end transformer encoder architecture called Performer to predict the expression values from DNA sequences. Proformer is…
Read More Unraveling Genetic Mysteries with Proformer: A Hybrid Macaron Transformer Model
AI | Bioinformatics | LLM | Medical Informatics | News | Paper Summary | Trending
Meet GigaPevt: The Next-Gen Medical Assistant Powered by Multimodal AI
ByAnchal Negi March 3, 2024October 22, 2026
Building a smart and helpful medical assistant through AI is challenging. The healthcare industry has several obstacles, such as the increasing costs and shortage of skilled employees, and reaching remote locations is difficult. Patients commonly talk to medical assistants for guidance and help these days. They often see them as computer helpers that seem human….
Read More Meet GigaPevt: The Next-Gen Medical Assistant Powered by Multimodal AI
AI | Algorithm | Bioinformatics | Drug Discovery | News | Tools | Trending
Eurofins Discovery Launches DiscoveryAI SAFIRE: A New AI Platform for Drug Discovery
ByDr. Tamanna Anwar March 3, 2024October 22, 2026
The drug discovery process is unduly time-consuming and expensive. Extensive laboratory testing is required to evaluate potential drug candidates for absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. Compounds that fail to meet acceptable thresholds for these properties may be unsafe or ineffective in humans, leading to high failure rates in clinical trials. But what if…
Read More Eurofins Discovery Launches DiscoveryAI SAFIRE: A New AI Platform for Drug Discovery
AI | Big Data | Bioinformatics | Data Analysis | LLM | News | Paper Summary | Trending
Can AI Assistants Crack Bioinformatics Challenges? A New Study Explores the Potential of Large Language Models
ByAnchal Negi March 2, 2024October 22, 2026
The scientific community may uncover the nature of life due to the great amount of biological data at its disposal. Implementing bioinformatics ensures converting this information into very valuable ones for decoding amino-acid sequences and the formation of new treatment strategies. However, the projects are big enough and need to be completed with modern techniques…
Read More Can AI Assistants Crack Bioinformatics Challenges? A New Study Explores the Potential of Large Language Models
AI | Bioinformatics | Genomics | LLM | News | Paper Summary | Trending
From Molecules to Genomes: Evo’s Trailblazing Approach to Sequence Modeling and Design
ByDeotima Chakraborty March 1, 2024October 22, 2026
The DNA, RNA, and proteins that control an organism’s entire functioning are all fully encoded in a sequence called the genome. Large-scale genome databases and machine learning advances may make it possible to create a biological foundation model that speeds up the generative design and mechanistic analysis of intricate molecular interactions. Researchers from Arc Institute, TogtherAI, and…
Read More From Molecules to Genomes: Evo’s Trailblazing Approach to Sequence Modeling and Design
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Structural Biology | Trending
PocketGen: A Novel Deep Generative Model for Designing Protein Binding Sites
ByDr. Tamanna Anwar March 1, 2024October 22, 2026
The ability to accurately model and redesign ligand binding sites (pockets) on protein surfaces holds tremendous value across fields like drug discovery, enzyme engineering, and biosensing. However, effectively generating protein pockets tailored to recognize user-defined small molecules has remained challenging. Recent research from the University of Science and Technology of China details PocketGen – an…
Read More PocketGen: A Novel Deep Generative Model for Designing Protein Binding Sites
AI | Bioinformatics | Cancer | LLM | Medical Informatics | News | Trending
Meet OncoGPT: Can This Medical Language Model Improve Communication and Support for Cancer Patients?
ByDr. Tamanna Anwar February 28, 2024October 22, 2026
OncoGPT is a customized language model created by Shenzhen Kanghua Juntai Biotech Co. Ltd. researchers in China that is intended to deliver precise medical recommendations for queries pertaining to oncology. Refined from more than 180K physician-patient exchanges, it offers precise guidance on questions about cancer. With its ability to alleviate the burden on healthcare providers…
Read More Meet OncoGPT: Can This Medical Language Model Improve Communication and Support for Cancer Patients?
AI | Bioinformatics | News | Paper Summary | Structural Biology | Tools | Trending
AlphaFLOW and ESMFLOW: A New Approach to Modeling Protein Ensembles with Combined Power of AlphaFold and Flow Matching
ByDeotima Chakraborty February 28, 2024October 22, 2026
Dynamic structural ensembles play a major role in the biological functions of proteins. For the purpose of learning and sampling the conformational landscapes of proteins, researchers create a flow-based generative modeling technique in this work. Sequence-conditioned generative models of protein structure are produced by optimizing the highly accurate single-state predictor AlphaFold technique within a unique…
Read More AlphaFLOW and ESMFLOW: A New Approach to Modeling Protein Ensembles with Combined Power of AlphaFold and Flow Matching
AI | Bioinformatics | Deep Learning | News | Paper Summary | Sequencing | Trending
Unlock the Potential of DeepMod2: A Deep Learning Framework for Precise DNA Methylation Analysis using Oxford Nanopore Sequencing
ByDeotima Chakraborty February 27, 2024October 22, 2026
Reduced representation methylation sequencing for CpG islands or imprinted areas is made possible by Oxford Nanopore sequencing, which offers a distinct advantage over other techniques by identifying DNA methylations from the ionic current signal of individual molecules. Here, scientists present DeepMod2, a thorough deep-learning framework that uses the ionic current signal from Nanopore sequencing to…
Read More Unlock the Potential of DeepMod2: A Deep Learning Framework for Precise DNA Methylation Analysis using Oxford Nanopore Sequencing
AI | Bioinformatics | Data Analysis | Gene Expression | Genomics | LLM | News | Paper Summary | Tools | Trending
Team of AI-made Scientists: A Groundbreaking System for Automating Scientific Discovery
ByAnchal Negi February 26, 2024October 22, 2026
Scientists from the University of Illinois, in collaboration with experts in the field, have unveiled a cutting-edge system named the “Team of AI-made Scientists.” This revolutionary development harnesses the power of large language models, effectively mimicking the capabilities of human data scientists to automate intricate analyses, such as the identification of disease genes. The research represents…
Read More Team of AI-made Scientists: A Groundbreaking System for Automating Scientific Discovery
AI | Bioinformatics | Knowledge Graph | LLM | News | Tools | Trending
LLMs in Biomedicine: Navigating the Future with the BioChatter Open-Source Solution
ByDr. Tamanna Anwar February 25, 2024October 22, 2026
BioChatter, a new open-source framework developed by Heidelberg University researchers and collaborators, aims to harness the power of large language models (LLMs) for biomedical research while ensuring responsible use. By integrating various functionalities like knowledge retrieval and model chaining, BioChatter simplifies LLM interaction for researchers, making it accessible and inclusive. It also emphasizes user-friendliness and…
Read More LLMs in Biomedicine: Navigating the Future with the BioChatter Open-Source Solution
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
Unlocking New Frontiers in Drug Design with PCMol: Integrating AlphaFold and De Novo Approaches
ByDeotima Chakraborty February 24, 2024October 22, 2026
Deep learning-based virtual screening provides a more effective way to find molecules that resemble drugs, and virtual sources give chemists useful information. Leiden University researchers present PCMol, a multi-target model that trains the de novo generative model on target proteins using the latent embeddings extracted from AlphaFold. Protein descriptors are a useful tactic for expanding…
Read More Unlocking New Frontiers in Drug Design with PCMol: Integrating AlphaFold and De Novo Approaches
AI | Bioinformatics | Health | Neural Network | News | Tools | Trending
Cracking the Code of Drug-Drug Interaction: DDIPrompt Unlocks a World of Safer Treatments
ByDr. Tamanna Anwar February 22, 2024October 22, 2026
Adverse drug-drug interactions (DDIs) pose a major health risk when using drug combinations to treat complex diseases. However, predicting harmful DDIs is extremely challenging due to the intricacies of modeling interactions between drug molecules. In a new preprint posted on arXiv, scientists from Fudan University, The Chinese University of Hong Kong, and the University of…
Read More Cracking the Code of Drug-Drug Interaction: DDIPrompt Unlocks a World of Safer Treatments
AI | Bioinformatics | News | Paper Summary | Proteomics | Structural Biology | Tools | Trending
AlphaFind: A New Frontier in Proteomic Exploration
ByDeotima Chakraborty February 22, 2024October 22, 2026
Effective structure-based search tools are necessary to efficiently organize the massive volume of data in the database. Novel tools like FoldSeek and 3D-surfer have been developed as a result of the inability of existing tools like PDBeFold to handle huge datasets. However, they are limited in their functionality by the fact that they can’t search…
Read More AlphaFind: A New Frontier in Proteomic Exploration
AI | Bioinformatics | Health | LLM | Medical Informatics | News | Trending
Improving Patient Care: The Role of Large Language Models in Doctors’ Notes Analysis
ByDr. Tamanna Anwar February 21, 2024October 22, 2026
The digitization of health records has enabled powerful AI techniques to extract key medical insights from the vast trove of unstructured clinical notes. However, real-world deployment of such models faces risks from dataset shifts. In a new study, Johns Hopkins and Columbia researchers leverage recent advances in language models to improve model robustness across different…
Read More Improving Patient Care: The Role of Large Language Models in Doctors’ Notes Analysis
AI | Bioinformatics | Chemoinformatics | Computational Models | Drug Discovery | LLM | News | Paper Summary | Trending
Revolutionizing Drug Discovery with ChemGLaM: Chemical-Genomics Language Models for Compound-Protein Interaction Prediction
ByDeotima Chakraborty February 21, 2024October 22, 2026
Compound-protein interaction (CPI) prediction accuracy is crucial for drug discovery. Creating deep learning models that can be applied broadly requires expanding the CPI data through experimental validation. With their strong generalization performance in a range of tasks involving substances and proteins, large language models (LLMs) such as chemical and protein language models have become foundational…
Read More Revolutionizing Drug Discovery with ChemGLaM: Chemical-Genomics Language Models for Compound-Protein Interaction Prediction
AI | Bioinformatics | Computational Models | News | Structural Biology | Tools | Trending
OpenFold Unveils SoloSeq and OpenFold-Multimer: Advancing AI in Protein Structure Analysis
ByDr. Tamanna Anwar February 20, 2024October 22, 2026
OpenFold, an artificial intelligence (AI) research consortium, has announced the release of two new tools that aim to improve protein structure prediction: SoloSeq and OpenFold-Multimer. These open-source tools represent important advances in integrating protein language models with structure prediction software, as well as modeling protein complexes more accurately. The SoloSeq model developed on Amazon Web…
Read More OpenFold Unveils SoloSeq and OpenFold-Multimer: Advancing AI in Protein Structure Analysis
AI | Bioinformatics | LLM | Machine Learning | News | Paper Summary | Proteomics | Trending
Unveiling DeepGO-SE: Advancing Protein Function Prediction Leveraging Language Models and GO Knowledge
ByDeotima Chakraborty February 19, 2024October 22, 2026
Gene Ontology is an axiomatic theory that describes the molecular roles, biological processes, and cellular placements of proteins using more than 100,000 axioms. Learning and reasoning skills are necessary for predicting the actions of proteins in order to preserve consistency and take advantage of prior knowledge. It is still difficult to apply all of the…
Read More Unveiling DeepGO-SE: Advancing Protein Function Prediction Leveraging Language Models and GO Knowledge
AI | Bioinformatics | Genomics | LLM | News | OMICS | Paper Summary
Meet DNABERT-S: Illuminating Genomic Diversity through Species-Aware DNA Embeddings
ByAnchal Negi February 18, 2024October 22, 2026
For scientists studying the functions of the genome, DNA embedding is a vital tool. Effective investigations like species categorization and metagenomics binning are made possible by converting unprocessed DNA sequences into comprehensible numerical representations. Modern embedding models, however, often require refinement, particularly when dealing with unlabeled data or sequences prone to errors. Researchers introduce DNABERT-S,…
Read More Meet DNABERT-S: Illuminating Genomic Diversity through Species-Aware DNA Embeddings
AI | Bioinformatics | Biomarker Discovery | Computational Models | Disease Diagnosis | News | Paper Summary | Trending
A Novel GNN Model ‘PathFormer’ Revolutionizes Highly Accurate Disease Diagnosis and Reproducible Biomarker Identification
ByDeotima Chakraborty February 17, 2024October 22, 2026
When analyzing omics data, regression analysis is an essential tool for identifying biomarkers. For the analysis of graph-structured data, graph neural networks (GNNs) are the most popular deep learning model. Their ability to consistently identify biomarkers across several datasets and their prediction accuracy is, nevertheless, limited. These difficulties arise from the distinct graph structure of…
Read More A Novel GNN Model ‘PathFormer’ Revolutionizes Highly Accurate Disease Diagnosis and Reproducible Biomarker Identification
AI | Bioinformatics | News | Proteomics | Structural Biology | Trending
Meet Proteus: Transforming the Landscape of Protein Design with Innovation and Efficiency
ByDr. Tamanna Anwar February 16, 2024October 22, 2026
Proteins perform essential functions in living organisms and adopt specific three-dimensional structures dictated by their amino acid sequences. The ability to accurately design novel protein structures from scratch could enable advances in areas like protein engineering and drug development. Recently, deep learning techniques like diffusion models have shown promise for generating designable protein structures without…
Read More Meet Proteus: Transforming the Landscape of Protein Design with Innovation and Efficiency
AI | Bioinformatics | Cancer Research | Genomics | Neural Network | News | Paper Summary | Precision Medicine | Trending
Beyond One-Size-Fits-All: Moffitt Unveils First Individualized Predictive Model for the Treatment of Multiple Myeloma
ByDeotima Chakraborty February 15, 2024October 22, 2026
Patients with recently diagnosed non-differentiated multiple myeloma (NDMM) have a wide range of outcomes, with overall survival (OS) spanning from several months to more than ten years. In this work, the researchers gathered a significant training set and a validation set of NDMM patients with clinical, demographic, genomic, and treatment data for the construction of…
Read More Beyond One-Size-Fits-All: Moffitt Unveils First Individualized Predictive Model for the Treatment of Multiple Myeloma
AI | Bioinformatics | Biotech | Genetic Engineering | LLM | News | Trending
Unlocking the Potential of RNA Design with Generative AI using GenerRNA
ByDr. Tamanna Anwar February 14, 2024October 22, 2026
A team of researchers from the University of Tokyo developed GenerRNA, the first large-scale pre-trained AI model for automated RNA design that does not require prior structural knowledge. Inspired by advances in protein language models, GenerRNA can generate a variety of RNAs for applications such as vaccines, therapeutics, and biotechnology. This model can generate new…
Read More Unlocking the Potential of RNA Design with Generative AI using GenerRNA
AI | Bioinformatics | Computational Models | Drug Discovery | LLM | News | Proteomics | Trending
GPCR-BERT: Revolutionizing GPCR Research with Protein Language Models
ByDr. Tamanna Anwar February 13, 2024October 22, 2026
Recent advances in large language models (LLMs) and transformers have opened new possibilities for modeling protein sequences as language. Carnegie Mellon University researchers have developed a new AI model called GPCR-BERT that leverages advances in natural language processing to uncover new insights into the sequence-function relationships in G protein-coupled receptors (GPCR), which are the target…
Read More GPCR-BERT: Revolutionizing GPCR Research with Protein Language Models
AI | Bioinformatics | Drug Discovery | LLM | News | Structural Biology | Tools | Trending
tFold Unveiled: A Swift and Accurate Approach to Antibody-Antigen Complex Modeling and Design
ByAnchal Negi February 13, 2024October 22, 2026
The soldiers of our immune system, antibodies, bind to specific targets like viruses and toxins and neutralize them. Predicting antibody-antigen complex structures accurately has the potential to significantly advance both the creation of therapeutic antibodies and scientific research. Traditional approaches are costly and slow, but an emerging technique called tFold (tFold-Ab and tFold-Ag) is rewriting…
Read More tFold Unveiled: A Swift and Accurate Approach to Antibody-Antigen Complex Modeling and Design
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Trending
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 | News | Structural Biology | Tools | Trending
Making AI-Driven Structural Biology Accessible with Foldy
ByDr. Tamanna Anwar February 11, 2024October 22, 2026
Recent breakthroughs in AI-based protein structure prediction have enormous potential to accelerate discoveries across the life sciences. However, major barriers persist in making these advanced tools accessible to non-experts without specialized computing resources. To address this gap, researchers from Joint BioEnergy Institute, US, have developed Foldy – an intuitive web application that puts powerful structural…
Read More Making AI-Driven Structural Biology Accessible with Foldy
AI | Bioinformatics | Biomarker Discovery | LLM | News | Paper Summary | Trending
MarkerGeneBERT: Revolutionizing Cell Marker Extraction Utilizing Natural Language Processing
ByAnchal Negi February 10, 2024October 22, 2026
MarkerGeneBERT, a natural language processing (NLP) system to automatically extract cell type markers from single-cell sequencing literature by parsing full text, was recently introduced by Scientists from CapitalBio Technology, China. MarkerGeneBERT compiled markers for 1733 human and 1832 mouse cell types across tissues, achieving 75% precision and 76% recall. This cell marker gene identification method…
Read More MarkerGeneBERT: Revolutionizing Cell Marker Extraction Utilizing Natural Language Processing
AI | Algorithm | Bioinformatics | News | Paper Summary | Structural Biology | Tools | Trending
CombFold: Advancing Structure Prediction of Large Protein Assemblies with Combinatorial Algorithms and AlphaFold2
ByDeotima Chakraborty February 9, 2024October 22, 2026
Deep learning models like RosettaFold and AlphaFold2 can predict protein structure with high accuracy; however, they still have difficulties when it comes to intricate connections between large proteins. To combat this problem, scientists from The Hebrew University of Jerusalem introduced CombFold, a hierarchical and combinatorial assembly technique that uses pairwise interactions between subunits predicted by…
Read More CombFold: Advancing Structure Prediction of Large Protein Assemblies with Combinatorial Algorithms and AlphaFold2
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 | Cancer Research | LLM | News | Paper Summary | Trending
reguloGPT Unleashed: GPT-Powered Knowledge Graphs Illuminate Molecular Regulatory Pathways
ByDeotima Chakraborty February 7, 2024October 22, 2026
Understanding biological processes and offering organized representations of intricate relationships are made possible by Knowledge Graphs, or KGs. However, the resources available today to mine KGs from biomedical literature are insufficient. Though they present a promising approach, large language models (LLMs) like GPT-4 have not yet been fully investigated in terms of their potential for…
Read More reguloGPT Unleashed: GPT-Powered Knowledge Graphs Illuminate Molecular Regulatory Pathways
AI | Bioinformatics | LLM | News | Paper Summary | Structural Biology | Trending
Has ESM-2 Truly Learned the Language of Protein Folding?
ByAnchal Negi February 6, 2024October 22, 2026
Protein structure prediction and design may be accomplished using protein language models (pLMs). They may not completely comprehend the biophysics of protein structures, though. The researchers from Harvard University provided an analysis of the structure prediction capabilities of the flagship pLM ESM-2. They developed an unsupervised method for comparing coevolutionary statistics to previous linear models…
Read More Has ESM-2 Truly Learned the Language of Protein Folding?
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 | News | Paper Summary | Proteomics | Tools | Trending
Revolutionizing Protein-protein Interaction Prediction with LazyAF: A Breakthrough Pipeline for Medium-scale In Silico Analysis
ByDeotima Chakraborty February 5, 2024October 22, 2026
Predicting protein structures has been transformed by artificial intelligence. However, rather than competence, accessibility, and ease of use are increasingly becoming limiting issues for end users as more sophisticated and powerful software is developed. In order to simplify the process of medium-scale protein-protein interaction prediction, the author Thomas C. McLean, from John Innes Centre, UK, presents…
Read More Revolutionizing Protein-protein Interaction Prediction with LazyAF: A Breakthrough Pipeline for Medium-scale In Silico Analysis
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 | Cancer | Neural Network | News | OMICS | Paper Summary | Precision Medicine | Trending
Meet IntegrAO: A Novel Unsupervised Framework for Integrating Incomplete Multi-omics Data and Patient Stratification
ByAnchal Negi February 3, 2024October 22, 2026
Advances in high-throughput omics profiling have improved cancer patient classification significantly. However, insufficient data in multi-omics integration is a big problem because conventional techniques like imputation and sample exclusion frequently jeopardize biological connections and diversity. Moreover, it is sometimes overlooked how important it is to appropriately classify newly diagnosed patients with incomplete omics data into…
Read More Meet IntegrAO: A Novel Unsupervised Framework for Integrating Incomplete Multi-omics Data and Patient Stratification
AI | Bioinformatics | LLM | News | Paper Summary | Proteomics | Trending
PepHarmony: An Integrated Sequence and Structure-based Peptide Encoding Framework Employing Multi-view Contrastive Learning
ByAnchal Negi January 31, 2024October 22, 2026
Gaining insight into the relationship of the Peptide sequence (the amino acid sequence) and their structure (the way they fold and interact) is a difficult task. Already existing methods are not up to the mark. Thanks to the ever-evolving field of protein language models for providing us with a new solution called PepHarmony. Developed by researchers…
Read More PepHarmony: An Integrated Sequence and Structure-based Peptide Encoding Framework Employing Multi-view Contrastive Learning
AI | Bioinformatics | Education | Machine Learning | News | Paper Summary | Proteomics | Trending
Empowering Researchers with ProteomicsML: An Online Oasis of Data Sets and Tutorials for Machine Learning in Proteomics
ByDeotima Chakraborty January 30, 2024October 22, 2026
The laborious aspects of acquiring and curating data sets for machine learning, especially in proteomics-based systems, present unique difficulties because there is a significant amount of data reduction from raw data to machine learning-ready data. In spite of the difficulties with accessibility and repeatability, laboratories frequently employ distinctive and intricate data processing pipelines to maximize…
Read More Empowering Researchers with ProteomicsML: An Online Oasis of Data Sets and Tutorials for Machine Learning in Proteomics

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