Researchers Develop Neural Network for Genomics that can Explain its Prediction...
A breakthrough by a group of researchers at New York University resulted in the development of an interpretable neural network that can explain the...
New Findings Challenge Traditional Rules of Genetics: UAA and UAG Codons...
Scientists from the Earlham Institute and the University of Oxford have unexpectedly altered our understanding of the rules of genetics while testing a new...
The Rise of mRNA Vaccines: A Game-Changer for Public Health?
The emergence of mRNA vaccine technology represents a monumental leap forward in disease prevention. A review article published in Nature Reviews Drug Discovery by...
A New Active Learning Model Makes Cellular Reprogramming and Genetic Intervention...
Millennia of evolution has allowed life to flourish in a million different ways, each suited to the niches it fills. The advent of CRISPR...
Massive Structural Clustering of the AlphaFold Database using Foldseek Cluster Reveals New...
Hundreds of millions of protein structures can be clustered using the new AI algorithm "Foldseek Cluster," which was developed by a team of researchers...
The Rise of Scientific Language Models: Revolutionizing Molecular Discovery
In a groundbreaking collaboration spanning IBM Research in Switzerland and the USA, scientists have illuminated the pivotal role of language models (LMs) in molecular...
Advancing Continuous Blood Pressure Monitoring: Accurate Measurements with Multichannel Sensing Signals...
Hypertension has long been known to be a causative factor for a multitude of medical ailments. Hypertension has further been noticed to have significantly...
GeneCompass: A New Foundation Model that Unlocks the Secrets of Gene...
A team of researchers from the University of Chinese Academy of Sciences, China, and collaborators developed GeneCompass, one of the first foundation models of...
IM3PACT: A New Computational Model to Improve the Design of Glucose-Responsive...
IM3PACT is a unique approach to improve MK-2640, glucose-responsive insulin (GRI). However, it did not function as well on humans as it did on...
The 2023 Nobel Prize in Physiology or Medicine: Pioneers Katalin Karikó...
The 2023 Nobel Prize in Physiology or Medicine has been jointly awarded to Katalin Karikó and Drew Weissman for their outstanding discoveries concerning nucleoside...
BigRNA: A Foundation Model for RNA Biology that Revolutionizes Personalized RNA...
A team of researchers at Deep Genomics Inc. developed BigRNA, a foundation model for understanding the biological functions and mechanisms of RNA molecules. Two...
Integrative Multi-Omics Analysis Reveals Molecular Responses to PARP Inhibition: A Focus...
Understanding diverse molecular mechanisms is necessary for the research of complex diseases. Using COSMOS, the integration of Thermal Proteome Profiling (TPP) with phosphoproteomics and...
Machine Learning Model ‘HASTEN’ Enables Giga-Scale Virtual Screening of Enumerated Chemical...
A team of researchers utilized HASTEN, a machine-learning (ML) model, to perform virtual screening on ultra-large chemical compound libraries. Several challenges are faced when...
Protein Engineering Tournament: A Competition Aiming to Revolutionize Computational Protein Design
Protein engineering is an emerging field in biological research – the improvement of existing proteins or the creation of new ones in order to...
Using EzMechanism to Unravel the Mysteries of Enzyme Catalysis
Enzyme mechanisms, intricate sequences of events within an enzyme's active site facilitating chemical reactions, are key to understanding enzyme function and evolution. Experimental approaches...
MitoSpace: A Novel Mitochondrial Phenotypic Atlas for Drug Discovery and Diagnostics
A collaborative effort between the Departments of Pharmacology, Chemistry, and Biochemistry at the University of California, San Diego, led to the development of MitoSpace,...
Streamlining Differential Expression Analysis on Bulk RNA-seq Data with PyDESeq2
Exploring bulk RNA-seq data has become a cornerstone for uncovering crucial insights into gene expression patterns and their relationship to phenotypes in biomedical research....
Achieving RNA’s AlphaFold Moment: How Close Are We?
AlphaFold's breakthrough in solving the protein structure prediction problem has ignited enthusiasm to apply similar methods to predict the 3D structures of RNAs. However,...
Accurate Annotation of Eukaryotic Genomes Made Easy: The BRAKER3 Advantage
Researchers from the University of Greifswald, Germany, introduced a new version of the BRAKER software BRAKER3, notably improving the annotation of eukaryotic genomes. Its...
DrugChat: A ChatGPT-like System for Drug Compound Discovery
A team of researchers at the University of California, San Diego, came together to develop a chatbot specifically catered to drug discovery called DrugChat....
Google’s DeepMind Unveils AlphaMissense: A Breakthrough AI Tool for Decoding Genetic...
Google's DeepMind scientists have made a monumental stride with the inception of AlphaMissense, an AI tool that can pinpoint genes responsible for diseases. This...
Machine Learning and Phylogenetic Analysis Join Forces to Predict Antibiotic Resistance...
Tuberculosis has been known to be a significant threat for many years now. Despite the development of a number of preventative strategies and medications,...
Meet DRfold: A Novel Method to Predict RNA Tertiary Structures with...
RNAs are essential components of physiological activities, however, accurately modeling their structures has long posed a challenge due to their complex structures. The National...
Meet AutoBA: A New Tool Making Bioinformatics Analysis Easy
Recent advancements in technology have now made it feasible for scientific researchers to be able to collect large amounts of biological data using a...
CodonBERT: A New Large Language Model Could Help Design Optimized mRNA...
A team of researchers at Digital R&D, Sanofi, USA, developed CodonBERT, a transformer-based large language model that is used for performing tasks related to...
Large Language Models Meet Single Cell Transcriptomics: Unlocking Biological Insights with...
Large language models, such as GPT (Generative Pre-trained Transformer), have showcased remarkable proficiency in various natural language processing tasks. Their ability to understand and...
Machine Learning Predicts Mood in Chronic Stroke Patients and Identifies the...
Stanford's scientists used Machine Learning to elucidate the relationship between stroke and depression by identifying a biomarker in stroke survivors. The findings may provide...
Virtual Drug Screening with Less Data: Boosting Predictions with Transfer Learning...
A team of researchers at the Eric and Wendy Schmidt Centre at the Broad Institute of MIT and Harvard developed a model that uses...
3Dmapper: A New Tool for Mapping Genetic Variants to Protein Structures...
Centuries after the first proteins were identified and characterized, their complexity proves a challenge for scientists all over the world. Their creation, evolution, and...
PeptideBERT: A Transformer-based Language Model for Predicting Peptide Properties using Amino...
Scientists at Carnegie Mellon University, USA, introduced PeptideBERT, a language model that is capable of predicting the properties of proteins and peptides solely based...
Deep Learning Powers New Methods for Protein Remote Homology Detection and...
Comprehending sequence–structure–function relationships is challenging for proteins with low similarity to existing proteins. New and improved alignment approaches are required for such proteins to...
Meet BARNACLE: A New Tool to Predict RNA Contacts using Data...
In the pursuit of understanding how RNA structure and function are related, predicting RNA structures becomes a tool alongside experimental approaches. However, the limited...
Meet HighFold: An AlphaFold-based Algorithm to Predict Cyclic Peptide Monomers and...
Cyclic peptides represent an emerging class of drugs that combine the advantageous attributes of small molecules with those of antibodies or protein-based therapeutics. Scientists...
Meet XVir: A Promising Transformer-based Approach to Spot Viral Reads in...
A team of researchers at The University of Texas at Austin developed a novel algorithm, XVir, that combines deep learning methods and transformers to...
Large Language Models Offering Solutions to Tackle Biological Complexity
Large Language Models (LLMs) have emerged as dynamic tools with the ability to transform the landscape of biological research in a world driven by...
Meet Flow: An Ultimate Bioinformatics Data Analysis and Management Solution
Scientists at King's College London, UK, and collaborators have introduced 'Flow,' an open-access web platform to perform bioinformatics analysis. Flow provides the capability to...
ChatGPT Empowers Clinical Decision Making with Impressive Accuracy
The large-language model (LLM)-based model, ChatGPT, had its clinical decision-making abilities put to the test in a joint study by researchers from Harvard Medical...
Revolutionizing Parkinson’s Care: Harnessing Artificial Intelligence to Detect Disease Severity at...
A team of researchers has recently developed an Artificial Intelligence (AI) based model for detecting the severity of the disease's progression and its symptoms...
Oxford Researchers Develop a Machine Learning Model to Predict 10-Year Breast...
A group of researchers affiliated with Oxford University, UK, have developed a prognostic model backed by the most extensive information set spanning a national,...
Meet FateMap: A Barcoding Approach to Decode Why Certain Cells Resist...
A collaborative research effort led by scientists and engineers at the University of Pennsylvania and Northwestern University led to the development of FateMap, a...
Decoding Thoughts into Words: A Breakthrough Brain-Computer Interface Lets Paralyzed Woman...
In a groundbreaking advancement, researchers from Stanford University have developed a speech brain-computer interface (BCI) that holds significant promise for individuals with paralysis. By...
From Algorithms to Antibiotics: Harnessing Artificial Intelligence in the Search for...
Faculties of the Mathematics Department at the University of Warsaw, Poland, have presented a review of the past two years progress of Artificial Intelligence...
Scientists Assemble the First Complete Human Y Chromosome Sequence: A Milestone...
The sequencing and assembly of the human Y chromosome have been challenging due to its intricate repeat structure, which encompasses lengthy palindromes, tandem repeats,...
Unveiling Cellular Secrets: Visualizing Dynamic Biomolecular Machinery with CryoDRGN-ET
The advancement of cryo-electron tomography (cryo-ET) has opened novel avenues for visualizing the intricate structures of dynamic macromolecular assemblies within their natural cellular surroundings....
AI’s Quantum Leap into Bioengineering: Unleashing Language Models in Atom-by-Atom Protein...
The University of Toronto researchers have explored the potential of Chemical Language Models (CLMs) to thrive as Biological Learning Models. In contrast to popular...
Stanford’s GEARS: An Innovative Approach to Predicting Transcriptional Outcomes of Multigene...
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,...
Meet DeepTracer-Refine: An Automated Refinement Approach for AlphaFold2 Predicted Protein Structures
Scientists of the DeepTracer project have formulated DeepTracer-refine, an automated pipeline that consolidates the advantages of sequence-to-model and map-to-model strategies, complements their shortcomings, and...
Meet OpenFold: Reimplementing AlphaFold2 to Illuminate Its Learning Mechanisms and Generalization
Columbia University and Harvard University researchers have developed OpenFold—a swift, memory-efficient, trainable AlphaFold2 implementation. They aimed to address the shortcomings of the revolutionary AlphaFold2,...
Tuft’s Researchers Unveil MELISSA: Revolutionizing Protein Function Prediction Through Semi-Supervised Embedding
Tufts University researchers have developed MELISSA, a groundbreaking approach for predicting protein functions through protein-protein association networks. Existing methods such as Mashup and deepNF...
Astrocyte-Powered Transformers: A Biological Blueprint for High-Performance Neural Architectures
Researchers affiliated with the MIT-IBM Watson AI Lab and Harvard Medical School have proposed a hypothesis of Transformer’s core computational schemes in order to...























































