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PocketGen: A Novel Deep Generative Model for Designing Protein Binding Sites

PocketGen: A Novel Deep Generative Model for Designing Protein Binding Sites

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The ability to accurately model and redesign ligand binding sites (pockets) on protein surfaces holds tremendous value across fields like drug discovery, enzyme engineering,...
Meet OncoGPT: Can This Medical Language Model Improve Communication and Support for Cancer Patients?

Meet OncoGPT: Can This Medical Language Model Improve Communication and Support...

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OncoGPT is a customized language model created by Shenzhen Kanghua Juntai Biotech Co. Ltd. researchers in China that is intended to deliver precise medical...
AlphaFLOW and ESMFLOW: A New Approach to Modeling Protein Ensembles with Combined Power of AlphaFold and Flow Matching

AlphaFLOW and ESMFLOW: A New Approach to Modeling Protein Ensembles with...

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Dynamic structural ensembles play a major role in the biological functions of proteins. For the purpose of learning and sampling the conformational landscapes of...
Unlock the Potential of DeepMod2: A Deep Learning Framework for Precise DNA Methylation Analysis using Oxford Nanopore Sequencing

Unlock the Potential of DeepMod2: A Deep Learning Framework for Precise...

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Reduced representation methylation sequencing for CpG islands or imprinted areas is made possible by Oxford Nanopore sequencing, which offers a distinct advantage over other...
A Team of AI Scientists: Novel Framework for Scientific Discovery from Gene Expression Data

Team of AI-made Scientists: A Groundbreaking System for Automating Scientific Discovery

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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."...
LLMs in Biomedicine: Navigating the Future with the BioChatter Open-Source Solution

LLMs in Biomedicine: Navigating the Future with the BioChatter Open-Source Solution

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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...
Unlocking New Frontiers in Drug Design: PCMol's Pioneering Integration of AlphaFold and De Novo Approaches

Unlocking New Frontiers in Drug Design with PCMol: Integrating AlphaFold and...

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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...
Unveiling Flexiplex: A New Tool for Demultiplexing and Sequence Searching in Omics Datasets

Unveiling Flexiplex: A Versatile and Fast Demultiplexing and Sequence Searching Tool...

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Omics datasets generated by high throughput sequencing contain vast amounts of nucleotide data that must be analyzed to extract meaningful biological insights. A common...
NIH's All of Us Research Program Unveils 275 Million New Genetic Variants, Boosting Precision Medicine Efforts

NIH’s All of Us Research Program Unveils 275 Million New Genetic...

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The All of Us Research Program, with its ambitious objective of creating a diverse cohort of one million volunteers and making their data available...
Cracking the Code of Drug-Drug Interaction: DDIPrompt Unlocks a World of Safer Treatments

Cracking the Code of Drug-Drug Interaction: DDIPrompt Unlocks a World of...

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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...
AlphaFind: A New Frontier in Proteomic Exploration

AlphaFind: A New Frontier in Proteomic Exploration

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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...
Improving Patient Care: The Role of Large Language Models in Doctors' Notes Analysis

Improving Patient Care: The Role of Large Language Models in Doctors’...

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The digitization of health records has enabled powerful AI techniques to extract key medical insights from the vast trove of unstructured clinical notes. However,...
Revolutionizing Drug Discovery with CHEMGLAM: Chemical-Genomics Language Models for Compound-Protein Interaction Prediction

Revolutionizing Drug Discovery with ChemGLaM: Chemical-Genomics Language Models for Compound-Protein Interaction...

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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...
OpenFold Unveils SoloSeq and OpenFold-Multimer: Advancing AI in Protein Structure Analysis

OpenFold Unveils SoloSeq and OpenFold-Multimer: Advancing AI in Protein Structure Analysis

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OpenFold, an artificial intelligence (AI) research consortium, has announced the release of two new tools that aim to improve protein structure prediction: SoloSeq and...
Accelerating Cancer Research: MuSiCal's Accurate and Sensitive Signature Analysis Paves the Way for Targeted Therapies

Accelerating Cancer Research: MuSiCal Offers Accurate and Sensitive Mutational Signature Analysis

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Cancer is a complex disease. It is brought on by the accumulation of several gene alterations. Understanding the patterns of these alterations, or mutational...
Unveiling DeepGO-SE: Advancing Protein Function Prediction Leveraging Language Models and GO Knowledge

Unveiling DeepGO-SE: Advancing Protein Function Prediction Leveraging Language Models and GO...

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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...
Meet DNABERT-S: Illuminating Genomic Diversity through Species-Aware DNA Embeddings

Meet DNABERT-S: Illuminating Genomic Diversity through Species-Aware DNA Embeddings

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For scientists studying the functions of the genome, DNA embedding is a vital tool. Effective investigations like species categorization and metagenomics binning are made...
A Novel GNN Model 'PathFormer' Revolutionizes Highly Accurate Disease Diagnosis and Reproducible Biomarker Identification

A Novel GNN Model ‘PathFormer’ Revolutionizes Highly Accurate Disease Diagnosis and...

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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...
University of Michigan Researchers Discover Novel Plant Protein Fold with Potential for Anti-Cancer Drugs

University of Michigan Researchers Discover Novel Plant Protein Fold with Potential...

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Researchers from the University of Michigan have reported the discovery of a new plant protein fold that catalyzes the formation of macrocyclic peptides through...
Meet Proteus: Transforming the Landscape of Protein Design with Innovation and Efficiency

Meet Proteus: Transforming the Landscape of Protein Design with Innovation and...

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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...
DANCE Unveils Hidden Depths of Protein Families Conformational Diversity through Molecular Motions

DANCE Unveils Hidden Depths of Protein Movement, Paving the Way for...

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One must understand proteins' structural flexibility in-depth to comprehend their role in biological processes and functional systems. It is still challenging to predict various...
Beyond One-Size-Fits-All: Moffitt Unveils First Individualized Predictive Model for the Treatment of Multiple Myeloma

Beyond One-Size-Fits-All: Moffitt Unveils First Individualized Predictive Model for the Treatment...

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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...
Unlocking the Potential of RNA Design with Generative AI using GenerRNA

Unlocking the Potential of RNA Design with Generative AI using GenerRNA

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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...
GPCR-BERT: Revolutionizing GPCR Research with Protein Language Models

GPCR-BERT: Revolutionizing GPCR Research with Protein Language Models

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Recent advances in large language models (LLMs) and transformers have opened new possibilities for modeling protein sequences as language. Carnegie Mellon University researchers have...
tFold Unveiled: A Swift and Accurate Approach to Antibody-Antigen Complex Modeling and Design

tFold Unveiled: A Swift and Accurate Approach to Antibody-Antigen Complex Modeling...

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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...
Choosing the Best Tool for Identifying Transcriptional Regulators: Navigating the NGS Landscape

Choosing the Best Tool for Identifying Transcriptional Regulators: Navigating the NGS...

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This article delves into a recent study undertaken by a team of researchers that examined multiple computer algorithms for transcriptional regulator prediction using Next-Generation...
Unveiling the Power of Deep-Learning: A Comprehensive Benchmark of Tertiary RNA Structure Prediction Methods

Unveiling the Power of Deep Learning: A Comprehensive Benchmark of Tertiary...

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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...
Making AI-Driven Structural Biology Accessible with Foldy

Making AI-Driven Structural Biology Accessible with Foldy

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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...
MarkerGeneBERT: Revolutionizing Cell Marker Extraction Utilizing Natural Language Processing

MarkerGeneBERT: Revolutionizing Cell Marker Extraction Utilizing Natural Language Processing

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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...
CombFold: Advancing Protein Complex Assembly Structure Prediction Harnessing Combinatorial Assembly Algorithm and AlphaFold2

CombFold: Advancing Structure Prediction of Large Protein Assemblies with Combinatorial Algorithms...

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Deep learning models like RosettaFold and AlphaFold2 can predict protein structure with high accuracy; however, they still have difficulties when it comes to intricate...
Unleashing nanoBERT: Revolutionizing Nanobody Therapeutics with Deep Learning

Unleashing nanoBERT: Revolutionizing Nanobody Therapeutics with Deep Learning

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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...
UChicago Scientists Crack the Code of HIV Entry into the Nucleus of the Cell: Could it Lead to New Treatment Strategies?

UChicago Scientists Crack the Code of HIV Entry into the Nucleus...

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In a major scientific breakthrough, researchers at the University of Chicago have succeeded in creating a comprehensive model of the nuclear pore complex with...
reguloGPT Unleashed: GPT-Powered Knowledge Graphs Illuminate Molecular Regulatory Pathways

reguloGPT Unleashed: GPT-Powered Knowledge Graphs Illuminate Molecular Regulatory Pathways

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Understanding biological processes and offering organized representations of intricate relationships are made possible by Knowledge Graphs, or KGs. However, the resources available today to...
Has ESM-2 Truly Learned the Language of Protein Folding?

Has ESM-2 Truly Learned the Language of Protein Folding?

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Protein structure prediction and design may be accomplished using protein language models (pLMs). They may not completely comprehend the biophysics of protein structures, though....
Revolutionize RNA Structure Prediction with RNA3DB: The Pinnacle Dataset for Training Deep Learning Models

Revolutionize RNA Structure Prediction with RNA3DB: The Pinnacle Dataset for Training...

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Harvard University researchers introduce RNA3DB, a dataset crafted from the Protein Data Bank (PDB), addressing challenges in RNA structure prediction. In response to limitations...

Revolutionizing Protein-protein Interaction Prediction with LazyAF: A Breakthrough Pipeline for Medium-scale...

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Predicting protein structures has been transformed by artificial intelligence. However, rather than competence, accessibility, and ease of use are increasingly becoming limiting issues for...
Unlocking the Enhancer Code: Deep Learning's Role in Designing Cell-specific Genetic Switches

Unlocking the Enhancer Code: Deep Learning’s Role in Designing Cell-specific Genetic...

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Transcriptional enhancers control the spatiotemporal activation of the target genes they regulate by serving as docking stations for various transcription factor combinations. It has...
Probing Ancestral Genomes Uncovers Unannotated Degenerate Transposable Elements Contributing to Gene Regulation and Expression

Probing Ancestral Genomes Uncovers Unannotated Degenerate Transposable Elements Contributing to Gene...

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Transposable elements (TEs) supply genomes with both coding and non-coding sequences and have significant roles in evolution. However, the extent of TE annotations in...
IntegrAO: A Novel Unsupervised Framework for Integrating Incomplete Multi-Omics Data and Patient Stratification

Meet IntegrAO: A Novel Unsupervised Framework for Integrating Incomplete Multi-omics Data...

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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...
Perturbation-response profiling for single cells.

Unlocking Cellular Mysteries with scPerturb: A Deep Dive into Harmonized Single-cell...

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Molecular and phenotypic responses to numerous perturbations are revealed by the increasing number of single-cell perturbation studies. However, variations in format, naming conventions, and...
Meet PepHarmony: An Integrated Sequence and Structure-based Peptide Encoding Framework Employing Multi-view Contrastive Learning

PepHarmony: An Integrated Sequence and Structure-based Peptide Encoding Framework Employing Multi-view...

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Gaining insight into the relationship of the Peptide sequence (the amino acid sequence) and their structure (the way they fold and interact) is a...
Empowering Researchers with ProteomicsML: An Online Oasis of Data Sets and Tutorials for Machine Learning in Proteomics

Empowering Researchers with ProteomicsML: An Online Oasis of Data Sets and...

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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...
The Human Immunome Project: Mapping the Global Landscape of Immune Diversity to Enhance Drugs and Vaccines

The Human Immunome Project: Mapping the Global Landscape of Immune Diversity...

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In a landmark initiative, the Human Immunome Project (HIP) commenced at a summit in La Jolla, California, bringing immunology specialists together to address the...
Unveiling ProtHyena: A Fast and Efficient Protein Language Model for Analysis at Single Amino Acid Resolution

Unveiling ProtHyena: A Fast and Efficient Protein Language Model for Analysis...

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The field of biological sequence analysis has lately benefited from the revolutionary changes brought about by the development of self-supervised deep language models for...
IntelliGenes Unveiled: A New Paradigm for AI-Driven Biomarker Discovery from Multi-Omic Data

IntelliGenes Unveiled: A New Paradigm for AI-Driven Biomarker Discovery from Multi-genomic...

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IntelliGenes is a new machine learning pipeline developed by researchers at The State University of New Jersey that integrates multi-genomics, clinical, and demographic data...
Meet Lingo3DMol: A Pocket-Based 3D Molecule Generation Method Harnessing the Power of Language Models and Geometric Deep Learning

Meet Lingo3DMol: A Pocket-based 3D Molecule Generation Method Leveraging Language Models...

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The drug development process involves a winding trail across the enormous chemical wilderness, looking for compounds that interact ideally with their target proteins. Traditional...
Unveiling the Future of Protein Design: RFdiffusion's De Novo Revolution

Unveiling the Future of Protein Design: RFdiffusion’s De Novo Revolution

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Protein design has seen significant progress, but a comprehensive deep-learning framework for protein design, including de novo binder design and higher-order symmetric architectures, remains...
AI reveals hidden immunogenicity determinants in MHC-peptide complexes

Cleveland Clinic and IBM’s Blueprint for Discovering Novel Immunotherapy Targets Using...

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Predicting the immunogenicity of peptide antigens attached to major histocompatibility complex (MHC) molecules is critical for developing new immunotherapies and better understanding human immune...
Transforming Protein Engineering with UW-Madison's Self-Driving Labs 'SAMPLE': A Cutting-edge, AI-driven Fully Autonomous Platform

Transforming Protein Engineering with UW-Madison’s Self-Driving Labs ‘SAMPLE’: A Cutting-edge, AI-driven...

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Although the field of protein engineering offers countless applications in chemistry, energy, and medicine, the process of designing new proteins with enhanced or unique...
Meet ChatDrug: A New ChatGPT-powered Conversational Drug Editing Framework

Meet ChatDrug: A New ChatGPT-powered Conversational Drug Editing Framework

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Drug discovery is one of the many fields where recent developments in conversational large language models (LLMs), like ChatGPT, have shown incredible promise. However,...

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Unveiling Bioinformatics Copilot 1.0: A Cutting-Edge LLM-Driven Solution for Transcriptomic Data Analysis

Unveiling Bioinformatics Copilot 1.0: A Cutting-Edge LLM-Driven Solution for Transcriptomic Data Analysis

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Single-cell transcriptomics has been generating large-scale information, improving our knowledge of cellular processes across different tissues, and facilitating medication discovery, diagnosis, and prognosis. But...
Decoding Proteins with DeProt: A Breakthrough in Language Modeling through Quantized Structure and Disentangled Attention

Decoding Proteins with DeProt: A Breakthrough in Language Modeling through Quantized Structure and Disentangled...

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Conventional representational models of protein functions have demonstrated notable performance in downstream tasks; nevertheless, they frequently do not incorporate explicit information on protein structure,...
Empowering Clinicians: How 'Tyche' Revolutionizes Medical Image Analysis with AI to Address Uncertainties

Empowering Clinicians: How ‘Tyche’ Revolutionizes Medical Image Analysis with AI to Address Uncertainties

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Just think about yourself as a physician examining an x-ray. You see an area that seems out of the ordinary, but you are unsure...
Unlocking Protein Co-regulation: How Genomic Language Models Illuminates Function Predictions

Unlocking Protein Co-regulation: How Genomic Language Models Illuminate Function Predictions

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Are you aware of the perception of a genomic language model? If not, then it's worth mentioning that researchers at Harvard, Cornell University, and...
A New Era in Interactomics: Exploring Predictomes, the AlphaFold-Modeled Protein Interaction Database

A New Era in Interactomics: Exploring Predictomes, the AlphaFold-Modeled Protein Interaction Database

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Imagine a teeming city where proteins are the movers and shakers. Each protein intertwines with others in partnerships that are vital to every cellular...