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DRUG-seq: A Game-Changing Approach to Transcriptional Profiling in Drug Discovery

The identification and comprehension of the mechanisms of potential drug compounds is a complex and expensive endeavor in the constantly changing pharmaceutical research landscape....

AI-Driven Macrocycle Design: How RFpeptides Generate High-Affinity Protein Binders for Diagnostics and Therapeutics

Large-scale screening techniques that are resource-intensive and offer limited control on binding mode are usually used to produce macrocyclic binders to therapeutic proteins. There...

Can InterPLM Decode the Hidden Language of Protein Modeling and Design AI?

The emergence of Protein Language Models (PLMs) is changing biological research for the better through efficient prediction of functional annotations and protein structures. However,...

Learning from Extremophiles: HyperMPNN’s Revolutionary Approach to Thermostable Protein Design

Recombinant proteins must be stable in order to be used in biotechnological or medicinal applications. Both the creation of new proteins and the stabilization...

Unlocking the Power of Single-cell RNA Sequencing with scExplorer

With its recent advancements, scRNA sequencing has enabled scientists to view the biological world at the most local of levels- the single cell. Thanks...

Seamless Multi-Omics Integration Made Easy with iModMix

Integrating metabolomics with other omics and providing insights into the biology of disease requires bioinformatics competence. Integration is difficult with present approaches, though, as...

Unlocking Chemical Space: TamGen’s Generative AI Approach for Target-Aware Molecule Generation in Drug Discovery

Novel compounds can be discovered in the wide chemical space due to generative drug design that enables one to develop molecules that are effective...

Exploring New Frontiers in SARS-CoV-2 Research with The Virtual Lab

When COVID-19 emerged as a global catastrophe, the scientists had only one goal: to come up with the possible treatments for the virus SARS-CoV-2,...

RhoFold+: Transforming RNA 3D Structure Prediction with Deep Learning

Although RNA 3D structures are important in understanding their functions and in the design of new drugs, their accurate prediction is still a challenge....

Unlocking the Secrets of RNA: How RNA-GPT is Transforming the Way We Explore and Understand RNA

RNAs are crucial molecules that convey genetic information necessary for life, and they have a big impact on biotechnology and medicine development. However, the...

From Concept to Reality: Efficient Protein Pocket Design with PocketGen

Protein pockets have been an integral part of drug discovery for several years and are also targeted during the design of novel molecules. Pockets...

Evo: A Genomics Foundation Model Redefining Sequence Modeling and Design

The DNA sequences of all living organisms hold the fundamental instructions for life. Massive datasets of entire genomes, together with machine learning advancements, may...

Innovating Through Collaboration: The Protein Engineering Tournament’s Impact on Computational Design

Protein engineering heavily relies on generating sequences using computational models. Limitations such as lack of benchmarking opportunities, scarcity of large protein function datasets, and...

How BALM is Redefining Binding Affinity Prediction for Unseen Targets and Drugs

In the fast-paced world of drug discovery, one of the most crucial aspects is understanding protein-ligand interactions. With the correct algorithms for predicting protein-ligand...

EPBDxDNABERT-2: A Multi-Modal Deep Learning Model for Enhanced Transcription Factor DNA Binding Prediction

It has been demonstrated that there is a functional correlation between transcriptional activity, thermodynamic stability, DNA breathing, and transcription factor (TF) binds. The researchers...

Omega-3 and Omega-6 Fatty Acids: New Allies in Cancer Prevention

A groundbreaking new research from the University of Georgia unveils that omega-3 and omega-6 fatty acids may play an integral role in cancer prevention,...

The Future of Bioinformatics: Building Expertise for Data-Driven Discovery

In an era where biological data grows exponentially, bioinformatics has emerged as a vital interdisciplinary field that combines biology, computer science, mathematics, and statistics....

The Power of Foundation Models in Pathology: How Paige’s Virchow is Changing Cancer Detection

Computational pathology is the evolution of cancer diagnosis into a new era, with the application of artificial intelligence to understand complex histopathology images. Generally,...

Unlock Molecular Conformations with Moltiverse Using Enhanced Sampling Molecular Dynamics Simulations

For drug development to be effective, it is essential to accurately predict the various bound-state conformations of small compounds, especially in situations where intricate...

AlphaFold3 Goes Open Source: A New Chapter in AI-Powered Protein Science

In a significant move for the scientific community, Google DeepMind has finally released the open-source code for AlphaFold3, their groundbreaking protein structure prediction tool....

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Harnessing AI for Molecular Discovery: The Promise of Molecular Dynamics Language Models

Harnessing AI for Molecular Discovery: The Promise of Molecular Dynamics Language Models

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Although molecular dynamics (MD) simulations provide accurate representations of the motion of molecular systems, molecular biology and materials science are challenged by the computational...
Decoding the Genetic Mechanism of B Chromosome Drive in Rye

Decoding the Genetic Mechanism of B Chromosome Drive in Rye

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The extra genetic material, which appears as 'B chromosomes,' has been a riddle for security for many species. They are of least concern for...
Streamlining High-Throughput Protein Complex Modeling with AlphaPulldown2

Streamlining High-Throughput Protein Complex Modeling with AlphaPulldown2

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AlphaPulldown version 2.0, a noteworthy computational biology program that transforms protein structure modeling, is presented by researchers from the European Molecular Biology Laboratory, Hamburg,...
The G2PT Model: Bridging the Gap Between Genotype and Phenotype Using Hierarchical Transformers

The G2PT Model: Bridging the Gap Between Genotype and Phenotype Using Hierarchical Transformers

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Gaining insight into the peculiar relationship between the genes we possess and the characteristics they express is undoubtedly one of the most intriguing quests...
Evolutionary Scale's ESM Cambrian: Revolutionizing Protein Understanding at the Scale of Life with Unsupervised Learning

Evolutionary Scale’s ESM Cambrian: Revolutionizing Protein Understanding at the Scale of Life with Unsupervised...

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Proteins are the most essential molecules for all forms of life on Earth. They perform a vast number of actions vital for life. However,...