Protein Function Prediction

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How Evolla is Deciphering the Molecular Language of Proteins with an 80 Billion Parameter Generative Model
ByDeotima Chakraborty January 14, 2025October 22, 2026

The complex molecular machinery that make up nature, proteins have evolved over billions of years and are essential to the continuation of life. However, a fundamental problem in contemporary biology is still interpreting their molecular language or comprehending how protein shapes and sequences encode and dictate biological functions. Here, scientists from Westlake University and Nankai…

Read More How Evolla is Deciphering the Molecular Language of Proteins with an 80 Billion Parameter Generative Model
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Protein Language Visualizer: A New Era of Sequence Similarity Exploration
ByDeotima Chakraborty December 16, 2024October 22, 2026

The availability of biological “big data” and the development of high-throughput sequencing technology have sped up the identification of new protein sequences, making it difficult to keep up with their functional annotation. Techniques like Sequence Similarity Networks (SSNs) have been used to visually arrange proteins for quicker identification in order to overcome this annotation difficulty….

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Advancing Protein Function Prediction: ProtEx’s Exemplars-based Retrieval-Augmented Approach
ByDeotima Chakraborty October 26, 2024October 22, 2026

The challenge of connecting a protein sequence to its fundamental biological function is becoming more and more significant in the field of biology. The retrieval-augmented protein function prediction method ProtEx, which uses database exemplars to increase accuracy and robustness and allow for generalization to unknown classes, is proposed by researchers from Google DeepMind in this…

Read More Advancing Protein Function Prediction: ProtEx’s Exemplars-based Retrieval-Augmented Approach
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Breaking New Ground in Protein Function Prediction with Protein-Mamba
ByAnchal Negi September 28, 2024October 22, 2026

Determining the function of proteins is one defining aspect of molecular biology that also carries great potential in drug discovery and development. A better comprehension of what the proteins do leads to faster discovery of valuable drug targets, which in turn saves the resources related to laboratory work, the purpose of which is the search…

Read More Breaking New Ground in Protein Function Prediction with Protein-Mamba
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Are We Closer to Mapping the Full Conformational Landscape of Proteins?
ByAnchal Negi September 5, 2024October 22, 2026

Proteins perform enormous tasks in our cells as molecular machines. These functions rely on the structural plasticity or the ability to adopt multiple shapes of the corresponding molecules. This is why knowledge of the conformational flexibility of proteins is very important in their function. A new tool, called Cfold, has been developed by scientists from…

Read More Are We Closer to Mapping the Full Conformational Landscape of Proteins?
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Oxford Researchers Breakthrough in Predicting Protein Function from Sequence Alone Using Statistics-Informed Graph Networks
ByDeotima Chakraborty August 17, 2024October 22, 2026

Understanding the complex mechanisms behind many essential biological activities is essential for developing new drugs and has broad ramifications in the disciplines of biotechnology, medicine, and drug development. Still, about 200 million proteins are uncharacterized, and computational attempts foresee annotations of different quality, mostly depending on protein structural information. Here, scientists describe a method for…

Read More Oxford Researchers Breakthrough in Predicting Protein Function from Sequence Alone Using Statistics-Informed Graph Networks
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No Coding Required! SaprotHub Brings Protein Modeling to Every Biologist
ByDeotima Chakraborty June 4, 2024October 22, 2026

Users without prior Machine Learning (ML) experience have difficulties when it comes to training and implementing deep learning models. Regardless of prior experience with machine learning, SaprotHub, introduced by the researchers of Westlake University, provides a simple platform for training, using, and exchanging protein models, encouraging cooperation among biologists. All it takes is a few…

Read More No Coding Required! SaprotHub Brings Protein Modeling to Every Biologist
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StarFunc: Revolutionizing Protein Function Prediction Leveraging Template-based and Deep Learning Approaches
ByAnchal Negi May 22, 2024October 22, 2026

A recent study by the Chengxin Zhang lab from the University of Michigan introduced StarFunc, an accurate protein function prediction approach integrating cutting-edge deep learning with template data from sequence homology, protein interactions, structural similarities, and domain families. Rather than picking sides, however, StarFunc combines two worlds to create a unified framework. This creative idea…

Read More StarFunc: Revolutionizing Protein Function Prediction Leveraging Template-based and Deep Learning Approaches
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Decoding Proteins with DeProt: A Breakthrough in Language Modeling through Quantized Structure and Disentangled Attention
ByDeotima Chakraborty April 22, 2024October 22, 2026

Conventional representational models of protein functions have demonstrated notable performance in downstream tasks; nevertheless, they frequently do not incorporate explicit information on protein structure, which is essential for comprehending the connection between protein sequences and functions. To fill this void, scientists provide DeProt, a Transformer-based protein language model that can take into account the shapes…

Read More Decoding Proteins with DeProt: A Breakthrough in Language Modeling through Quantized Structure and Disentangled Attention
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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
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Tuft’s Researchers Unveil MELISSA: Revolutionizing Protein Function Prediction Through Semi-Supervised Embedding
ByNeegar Naushaba Iqbal August 20, 2023August 29, 2023

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 employ network diffusion analysis and structure embedding of proteins, respectively, but they neglect to utilize known protein functions directly. Contrarily, MELISSA, a novel approach, incorporates functional labels during the embedding stage….

Read More Tuft’s Researchers Unveil MELISSA: Revolutionizing Protein Function Prediction Through Semi-Supervised Embedding
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Meta’s AI Protein Structure Prediction Model ‘ESMFold’ Predicts as Accurately and 6x Faster than AlphaFold2
BySrishti Sharma August 13, 2022October 6, 2022

Researchers at Meta AI developed an artificial intelligence (AI) model that can precisely predict entire atomic protein structures from a single sequence of a protein. The use of language model representations to replace the requirement for explicit homologous sequences distinguishes ESMFold from AlphaFold2. As a result of this simplification, ESMFold is significantly faster than the…

Read More Meta’s AI Protein Structure Prediction Model ‘ESMFold’ Predicts as Accurately and 6x Faster than AlphaFold2
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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

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Protein Function Prediction

Protein Function and Properties Characterization Using Language Models

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