Language Models

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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 | 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 | 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 | 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 | 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 | 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 | 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 | Computational Models | LLM | News | Paper Summary | Proteomics | Trending

Unveiling ProtHyena: A Fast and Efficient Protein Language Model for Analysis at Single Amino Acid Resolution
ByDeotima Chakraborty January 28, 2024October 22, 2026

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 natural language processing tasks. Conventional models show significant effectiveness in a variety of applications. These models are mostly based on the Transformer and BERT architectures. However, the quadratic computational complexity O(L2)…

Read More Unveiling ProtHyena: A Fast and Efficient Protein Language Model for Analysis at Single Amino Acid Resolution
AI | Bioinformatics | Deep Learning | Drug Discovery | LLM | News | Paper Summary | Structural Biology | Trending

Meet Lingo3DMol: A Pocket-based 3D Molecule Generation Method Leveraging Language Models and Geometric Deep Learning
ByAnchal Negi January 27, 2024October 22, 2026

The drug development process involves a winding trail across the enormous chemical wilderness, looking for compounds that interact ideally with their target proteins. Traditional approaches, while successful, frequently stumble in the dark, unable to capture the delicate 3D pattern of particles and their interactions. But do not worry; scientists from Beijing StoneWise Technology Co Ltd, …

Read More Meet Lingo3DMol: A Pocket-based 3D Molecule Generation Method Leveraging Language Models and Geometric Deep Learning
AI | Bioinformatics | LLM | Neuroscience | News | Trending

Unlocking Brain Mysteries with BrainLM: A Versatile Foundation Model for Recording Brain Activity
ByDeotima Chakraborty January 21, 2024January 21, 2024

The Brain Language Model (BrainLM), a foundation model for brain activity dynamics trained on 6,700 hours of functional magnetic resonance imaging (fMRI) scans, was introduced by researchers at Yale University. Through self-supervised masked-prediction training, BrainLM exhibits high performance on zero-shot inference and fine-tuning tasks. Accurate prediction of future brain states and clinical variables such as…

Read More Unlocking Brain Mysteries with BrainLM: A Versatile Foundation Model for Recording Brain Activity
AI | Bioinformatics | Drug Discovery | LLM | Machine Learning | News | Paper Summary | Structural Biology | Trending

The Rise of Scientific Language Models: Revolutionizing Molecular Discovery
BySwasti Tyagi October 6, 2023October 22, 2026

In a groundbreaking collaboration spanning IBM Research in Switzerland and the USA, scientists have illuminated the pivotal role of language models (LMs) in molecular discovery. It has been determined that transformer-based architectures are the most popular forms of language models, enabling their widespread use in various domains of science. Due to this, the term ‘scientific…

Read More The Rise of Scientific Language Models: Revolutionizing Molecular Discovery
Bioinformatics | Computational Models | Data Science | Deep Learning | Machine Learning | News | Paper Summary | Proteomics

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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Language Models

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

Protein Function and Properties Characterization Using Language Models

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