Proteomics

Proteomics and protein bioinformatics: mass spectrometry analysis, protein–protein interactions and protein function.

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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
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Unveiling the Future of Protein Design: RFdiffusion’s De Novo Revolution
ByDeotima Chakraborty January 26, 2024October 22, 2026

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 unexplored. Diffusion models have shown success in image and language generative modeling but have limited success in protein modeling due to the complexity of protein backbone geometry and sequence-structure relationships. The…

Read More Unveiling the Future of Protein Design: RFdiffusion’s De Novo Revolution
AI | Bioengineering | Bioinformatics | News | Paper Summary | Proteomics | Trending

Transforming Protein Engineering with UW-Madison’s Self-Driving Labs ‘SAMPLE’: A Cutting-edge, AI-driven Fully Autonomous Platform
ByDeotima Chakraborty January 24, 2024October 22, 2026

Although the field of protein engineering offers countless applications in chemistry, energy, and medicine, the process of designing new proteins with enhanced or unique functionalities is still labor-intensive, slow, and ineffective. The Self-driving Autonomous Machines for Protein Landscape Exploration (SAMPLE) platform for completely autonomous protein engineering is presented here by researchers from the University of…

Read More Transforming Protein Engineering with UW-Madison’s Self-Driving Labs ‘SAMPLE’: A Cutting-edge, AI-driven Fully Autonomous Platform
Bioinformatics | Cancer | Cancer Research | News | Paper Summary | Proteomics | Structural Biology | Trending

The Glue that Heals: St. Jude’s Researchers Unveil Molecular ‘Super-Glue’ Propelling Innovative Cancer Drug Development
ByAnchal Negi January 20, 2024January 21, 2024

Scientists at St. Jude Children’s Research Hospital have published their findings on SJ3149, a chemical with broad efficacy against various cancer types, particularly acute myeloid leukemia (AML). Scientists worked together to discover and improve a chemical molecule that functions as a molecular “super-glue” for a variety of tumors. SJ3149 binds to cancer-related protein casein kinase…

Read More The Glue that Heals: St. Jude’s Researchers Unveil Molecular ‘Super-Glue’ Propelling Innovative Cancer Drug Development
Bioinformatics | Drug Discovery | News | Paper Summary | Proteomics | Structural Biology | Trending

Scripps Scientists Develop High-Resolution Method to Uncover Druggable Sites on Proteins
BySonal Keni January 10, 2024October 22, 2026

The factors at play in the binding of proteins are intricate and hard to untangle – despite great advancements in recent years in humanity’s understanding of the proteome, conventional methods for determining binding sites and uncovering the mechanisms that influence small molecule-protein binding remain difficult, resource-intensive, and expensive. Computational biology may provide a more efficient…

Read More Scripps Scientists Develop High-Resolution Method to Uncover Druggable Sites on Proteins
Bioinformatics | Disease Diagnosis | Health | Machine Learning | Medical Informatics | News | Paper Summary | Precision Medicine | Proteomics | Trending

Stanford Medicine Scientists Inch Closer to Predicting Which of Our Organs Will Fail First
ByDeotima Chakraborty December 14, 2023December 14, 2023

In a recently published study, Stanford Medicine researchers highlighted age-related problems in humans and showed how aging varies from person to person and between organs within an individual. Researchers used human blood plasma protein levels from particular organs to examine aging in 11 key organs in real people. The approach suggested by the authors offers…

Read More Stanford Medicine Scientists Inch Closer to Predicting Which of Our Organs Will Fail First
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Analyzing Bio-Ontologies Made Easy: A Deep Dive into simona R Package for Semantic Similarity
ByDr. Tamanna Anwar December 9, 2023December 9, 2023

As modern biology embraces high-throughput genomics and multi-omics profiling, the torrents of data now routinely generated necessitate improved systems organizing information to enable meaningful interpretations. Computational ontologies serve crucial roles, formalizing knowledge into structured controlled vocabularies interconnecting concepts hierarchically. However, deriving insights from these intricate semantic networks at scale remains challenging. Seeking to empower ontology-driven…

Read More Analyzing Bio-Ontologies Made Easy: A Deep Dive into simona R Package for Semantic Similarity
Bioinformatics | News | OMICS | Proteomics | Tools | Trending

Meet Multiple Protein Profiler: A New Tool for Analyzing Proteomic Datasets
ByDr. Tamanna Anwar December 8, 2023October 22, 2026

Dalhousie University, Canada researchers have developed a new web-based tool called Multiple Protein Profiler (MPP) that can efficiently calculate 12 key physicochemical properties of multiple protein sequences uploaded by users. Existing protein analysis tools are limited to single sequences, but MPP enables high-throughput batch analysis of entire proteomic datasets. The computed parameters provide insights into…

Read More Meet Multiple Protein Profiler: A New Tool for Analyzing Proteomic Datasets
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Paper Summary | Proteomics | Structural Biology | Trending

Decoding the Protein-Ligand Enigma: A Deep Dive into Deep Learning Approaches for Binding Affinity Prediction
ByDeotima Chakraborty November 30, 2023November 30, 2023

Researchers from the University of Edinburgh, UK, explore the impact of ligand and protein encodings on binding affinities prediction for different data sets, a crucial aspect of drug development and discovery. Sequence-based deep learning, convolutional neural network-based encodings, and graph neural network-based encodings were used to investigate protein roles. Graph-neural networks were used to construct…

Read More Decoding the Protein-Ligand Enigma: A Deep Dive into Deep Learning Approaches for Binding Affinity Prediction
AI | Bioinformatics | News | OMICS | Paper Summary | Proteomics | Structural Biology | Tools | Trending

Enlightening the Proteomic Space with Chroma: A Revolutionary Generative Model for Protein Design
ByDr. Tamanna Anwar November 21, 2023October 22, 2026

Proteins are incredible molecules that carry out nearly every function necessary for life. However, their staggering complexity has made designing new proteins an immensely difficult challenge. Now, AI is poised to change that. Scientists have developed Chroma, a groundbreaking AI system that can generate completely novel protein structures and sequences from scratch. This innovation could…

Read More Enlightening the Proteomic Space with Chroma: A Revolutionary Generative Model for Protein Design
Bioinformatics | News | Paper Summary | Phylogenetic Analysis | Proteomics | Structural Biology | Trending

Meet A3D-MODB: A New Database for Predicting Protein Aggregation in Model Organisms
BySonal Keni November 13, 2023October 22, 2026

The Protein Folding and Computational Diseases Group at IBB-UAB, in collaboration with researchers from the University of Warsaw, developed a new database, A3D-MOBD (A3D Model Organism Database), that collects information regarding proteomes from 12 of the key model organisms for biological research as well as protein structure predictions to form the most comprehensive resource on…

Read More Meet A3D-MODB: A New Database for Predicting Protein Aggregation in Model Organisms
AI | Bioinformatics | News | Proteomics | Structural Biology | Tools | Trending

The AlphaFold Revolution Continues: Unraveling the Next-Gen Advancements
BySonal Keni November 6, 2023October 22, 2026

The introduction of AlphaFold 2 was a groundbreaking breakthrough in the field of predicting protein structures and interactions. Google’s DeepMind, was the driving force behind this tool, which used deep learning methods in order to successfully predict the structures of various proteins. Described by many experts in the field as one of the most transformational…

Read More The AlphaFold Revolution Continues: Unraveling the Next-Gen Advancements
News | Paper Summary | Proteomics | Sequencing | Structural Biology | Trending

Demystifying the Genetic Architecture of Proteins through Experimental Models
BySwasti Tyagi November 3, 2023January 24, 2024

A collaborative effort between researchers from the UK, Spain, and Germany utilized experimental methods to explore amino acid sequence spaces and demonstrated that for a decent number of proteins, genetic architecture can be relatively simple. They also noted that models based on artificial intelligence that are conventionally used for biological prediction purposes can be much…

Read More Demystifying the Genetic Architecture of Proteins through Experimental Models
Bioengineering | Bioinformatics | News | Proteomics | Structural Biology | Tools | Trending

Illuminating the Complexity of Interactions within and between Proteins and Ligands with Surfaces
ByDr. Tamanna Anwar November 2, 2023October 22, 2026

Computational methods have revolutionized our understanding of molecular interactions and their pivotal role in the stability of biomolecular structures and complexes. These insights are crucial for modulating, engineering, and comprehending biological processes. Scientists from the Université de Montréal, Canada, introduce Surfaces, a groundbreaking software that offers a seamless, fast, and highly customizable approach to quantify…

Read More Illuminating the Complexity of Interactions within and between Proteins and Ligands with Surfaces
AI | Bioinformatics | Deep Learning | Neural Network | News | Paper Summary | Proteomics | Trending

A New Deep Neural Networks-Based Method Predicts Protein Abundance Based on Amino Acid Sequence
BySonal Keni October 12, 2023November 24, 2023

With the potential to have significant impacts on various fields, like therapeutics and agritech, protein engineering has recently been a subject that has incited much intrigue within the scientific community. However, despite this, many factors that govern the synthesis and regulation of proteins aren’t well-known. The intricate relationships that influence the various interactions proteins have…

Read More A New Deep Neural Networks-Based Method Predicts Protein Abundance Based on Amino Acid Sequence
AI | Bioinformatics | Machine Learning | News | Paper Summary | Proteomics | Structural Biology | Trending

Protein Engineering Tournament: A Competition Aiming to Revolutionize Computational Protein Design
BySonal Keni September 29, 2023October 22, 2026

Protein engineering is an emerging field in biological research – the improvement of existing proteins or the creation of new ones in order to improve efficiency or perform new functions has proved to be a field with much potential. Despite advancements in the field making protein engineering a sought-after field for industrial applications, it is…

Read More Protein Engineering Tournament: A Competition Aiming to Revolutionize Computational Protein Design
AI | Disease Diagnosis | Health | Machine Learning | News | Paper Summary | Proteomics | Structural Biology | Tools | Trending

Google’s DeepMind Unveils AlphaMissense: A Breakthrough AI Tool for Decoding Genetic Enigmas
ByPrachi Khare September 22, 2023September 23, 2023

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 move signals substantial progress in gene research and potentially transforms how rare genetic disorders are detected. The state-of-the-art capacities of AlphaMissense gear towards improving our grasp on intricate genetic changes, thus…

Read More Google’s DeepMind Unveils AlphaMissense: A Breakthrough AI Tool for Decoding Genetic Enigmas
Bioinformatics | News | Paper Summary | Proteomics | Structural Biology | Tools | Trending

3Dmapper: A New Tool for Mapping Genetic Variants to Protein Structures at BioBank Scale
BySonal Keni September 15, 2023October 22, 2026

Centuries after the first proteins were identified and characterized, their complexity proves a challenge for scientists all over the world. Their creation, evolution, and many variations are questions for which we have only just begun to uncover the answers. A new bioinformatics tool has now been developed that can provide researchers with a way to…

Read More 3Dmapper: A New Tool for Mapping Genetic Variants to Protein Structures at BioBank Scale
AI | Bioengineering | Bioinformatics | LLM | News | OMICS | Paper Summary | Proteomics | Trending

PeptideBERT: A Transformer-based Language Model for Predicting Peptide Properties using Amino Acid Sequences
BySwasti Tyagi September 14, 2023September 14, 2023

Scientists at Carnegie Mellon University, USA, introduced PeptideBERT, a language model that is capable of predicting the properties of proteins and peptides solely based on sequences provided to it without requiring structural data. In this study, activities related to hemolysis, non-fouling, and solubility of peptides are taken into consideration for predicting the proteins. The model…

Read More PeptideBERT: A Transformer-based Language Model for Predicting Peptide Properties using Amino Acid Sequences
Bioinformatics | Deep Learning | Education | News | OMICS | Paper Summary | Proteomics | Tools | Trending

Deep Learning Powers New Methods for Protein Remote Homology Detection and Structural Alignment
ByPrachi Khare September 12, 2023October 22, 2026

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 find their similarity to previously annotated sequences. To close this gap, scientists from New York University, USA, developed two cutting-edge deep learning methods: TM-Vec and DeepBLAST. The search for structural similarities…

Read More Deep Learning Powers New Methods for Protein Remote Homology Detection and Structural Alignment
Algorithm | Bioinformatics | Drug Discovery | News | Paper Summary | Proteomics | Structural Biology | Tools | Trending

Meet HighFold: An AlphaFold-based Algorithm to Predict Cyclic Peptide Monomers and Complexes with Precision
BySwasti Tyagi September 9, 2023September 9, 2023

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 from the College of Pharmaceutical Sciences at the Zhejiang University of Technology and Shanghai Highslab Therapeutics have introduced HighFold, an improved method for predicting cyclic peptide monomers and complex structures. It…

Read More Meet HighFold: An AlphaFold-based Algorithm to Predict Cyclic Peptide Monomers and Complexes with Precision
AI | Bioengineering | Bioinformatics | Chemoinformatics | News | Paper Summary | Proteomics | Trending

AI’s Quantum Leap into Bioengineering: Unleashing Language Models in Atom-by-Atom Protein Generation
ByAditi Sarkar August 24, 2023August 24, 2023

The University of Toronto researchers have explored the potential of Chemical Language Models (CLMs) to thrive as Biological Learning Models. In contrast to popular Protein Language Models that learn from protein sequences, CLMs can learn atomic-level representations of proteins and also learn protein backbones and natural amino acid structures, as well as the primary sequence…

Read More AI’s Quantum Leap into Bioengineering: Unleashing Language Models in Atom-by-Atom Protein Generation
AI | Bioinformatics | News | Paper Summary | Proteomics | Structural Biology | Tools | Trending

Meet OpenFold: Reimplementing AlphaFold2 to Illuminate Its Learning Mechanisms and Generalization
ByNeegar Naushaba Iqbal August 21, 2023August 29, 2023

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, which, despite predicting protein structures with remarkable accuracy and dramatically advancing structural biology, lacked accessible code and training data. This lack limits progress in various areas, such as tackling new tasks…

Read More Meet OpenFold: Reimplementing AlphaFold2 to Illuminate Its Learning Mechanisms and Generalization
AI | Bioinformatics | Machine Learning | News | Paper Summary | Proteomics | Tools | Trending

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
AI | Bioinformatics | Genomics | Machine Learning | News | OMICS | Paper Summary | Proteomics | Tools | Trending

Machine Learning Magic: DNABERT-2 Empowers Enhanced Multi-Species Genomic Analysis
ByNeegar Naushaba Iqbal July 28, 2023October 22, 2026

The key to unlocking genomic secrets is here. Researchers from Northwestern University, in collaboration with Stony Brook University, have developed DNABERT-2, which is a better alternative to the previously used foundation models, DNABERT and Nucleotide Transformer. These models worked by breaking genomic sequences into fixed-size k-mers, which takes a toll on computing efficiency. However, DNABERT-2…

Read More Machine Learning Magic: DNABERT-2 Empowers Enhanced Multi-Species Genomic Analysis
AI | Bioinformatics | News | Paper Summary | Proteomics | Structural Biology | Trending | Virus

A Synergistic Approach: AlphaFold and Symmetrical Docking for Precise Protein Assembly Structure Prediction
ByAditi Sarkar July 4, 2023July 4, 2023

Mads Jeppesen and Ingemar André from Lund University, Sweden, have demonstrated a protein complex assembly structure prediction pipeline conjugating Alphafold and symmetrical docking method. The approach makes structural apprehension of large multi-chain assembly of nature’s most complex symmetrical systems, the cubic symmetric group including tetrahedra, octahedra, and icosahedra, feasible at the atomic level. The proposed…

Read More A Synergistic Approach: AlphaFold and Symmetrical Docking for Precise Protein Assembly Structure Prediction
AI | Bioinformatics | COVID-19 | Covid-19 News | Drug Discovery | Machine Learning | News | Proteomics | SARS-CoV-2 | Structural Biology | Trending

AI-Powered Protein-Protein Interaction Drug Discovery Pipeline Yields a Promising SARS-CoV-2 Inhibitor
ByAditi Sarkar June 24, 2023June 24, 2023

The multi-adaptive Support Vector Machine Learning Algorithm (maSVM) can improve comparisons between binary Protein-Protein interaction datasets gathered in different laboratories and can be utilized to confidently prioritize potential targets for Protein-Protein Interaction (PPI) based drug discovery. The researchers first showed that the automatic classification of large quantitative interaction datasets could be performed with high confidence….

Read More AI-Powered Protein-Protein Interaction Drug Discovery Pipeline Yields a Promising SARS-CoV-2 Inhibitor
Bioinformatics | Cancer Research | Disease Diagnosis | Genomics | News | Proteomics | Trending

Exploring Molecular Alterations in Cancer with cProSite: A Web-based Tool for Genomics, Proteomics, and Phosphoproteomics Data Analysis
ByDr. Tamanna Anwar June 19, 2023October 22, 2026

Large-scale proteome and genomic investigations play a crucial role in understanding the molecular causes of cancer. The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) has developed an invaluable resource of data, cProSite (Cancer Proteogenomic Data Analysis Site), a user-friendly website designed for biologists and clinicians, offering online analysis of genomics, proteomics, and phosphoproteomics using CPTAC…

Read More Exploring Molecular Alterations in Cancer with cProSite: A Web-based Tool for Genomics, Proteomics, and Phosphoproteomics Data Analysis
AI | Bioinformatics | Deep Learning | News | Proteomics | Structural Biology | Trending

Enhancing Protein Complex Structure Modeling: Deep Learning Meets Crosslinking Mass Spectrometry
ByDr. Tamanna Anwar June 13, 2023October 22, 2026

Protein complex structures form the foundation for understanding the complexities of molecular biology. While deep learning-based methods have significantly enhanced the prediction of single protein structures, predicting the structures of protein complexes remains a challenge. This challenge arises from the limited availability of structural and evolutionary information for protein complexes. However, recent breakthroughs have incorporated…

Read More Enhancing Protein Complex Structure Modeling: Deep Learning Meets Crosslinking Mass Spectrometry
AI | Bioinformatics | Cloud Computing | Computational Models | Deep Learning | News | Paper Summary | Proteomics | Trending

Serverless Deep Learning Models for Peptide Property Prediction: Achieving State-of-the-Art Results without Cloud Dependencies
ByAditi Sarkar June 10, 2023October 22, 2026

Researchers at the Chemical Engineering Department of the University of Rochester, New York, introduce three deep learning sequence-based models for peptide properties prediction implementing a Recurrent Neural Network to compute hemolysis, solubility & nonfouling features of peptides from their sequences in a serverless architecture intending for better accessibility and to endorse open science. The sequence-based…

Read More Serverless Deep Learning Models for Peptide Property Prediction: Achieving State-of-the-Art Results without Cloud Dependencies
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Proteomics | Tools | Trending

Advancing Protein Subcellular and Suborganellar Localization Prediction and Visualization with MULocDeep
ByAditi Sarkar June 6, 2023October 22, 2026

Researchers at the University of Missouri upgraded the MULocDeep web application by integrating animal, fungi, and plant species-specific models that meet competitive performance at the subcellular level against contemporary state-of-the-art methods and thus hold promising prospects in speeding up research in various domains, including drug development. Harnessing the power of Artificial Intelligence MULocDeep covers comprehensive…

Read More Advancing Protein Subcellular and Suborganellar Localization Prediction and Visualization with MULocDeep
Bioinformatics | Machine Learning | Metagenomics | News | Paper Summary | Proteomics | Tools | Trending

Meet Snekmer: A Powerful Machine Learning Based Protein Annotation Tool Utilizing Peptide Fingerprinting
ByDr. Tamanna Anwar June 5, 2023June 5, 2023

Snekmer, an innovative software developed to better understand protein function in microbes, emerged from the collaborative efforts of researchers from the Pacific Northwest National Laboratory, Baylor University, and Oregon Health & Science University. This cutting-edge tool harnesses the power of short protein sequences, known as kmers, to generate protein family models through machine learning techniques….

Read More Meet Snekmer: A Powerful Machine Learning Based Protein Annotation Tool Utilizing Peptide Fingerprinting
Bioinformatics | Drug Discovery | News | Paper Summary | Proteomics | Trending

Exploring Protein Modifications in Metabolic Diseases: Molecular Mechanisms and Therapeutic Strategies
ByAditi Sarkar June 2, 2023October 22, 2026

Comprehensive introspection of cellular and molecular level aberrations that prompted the worldwide prevalence of life-threatening Non Communicable Diseases like Diabetes, Obesity, Hypertension, Nonalcoholic Fatty Liver Disease (NAFLD), CDV (Cardiovascular diseases), etc. is an acute need towards their prohibition, effective clinical treatment, control, and remedy. Decoding the intricate details, cascade, and consequences of protein post translational…

Read More Exploring Protein Modifications in Metabolic Diseases: Molecular Mechanisms and Therapeutic Strategies
AI | Cell | News | Paper Summary | Proteomics | Trending

Fast and Accurate Imaging of Proteins in Cells with TomoTwin: A Novel AI-based Software
ByBanhita Maitra May 18, 2023May 21, 2023

Scientists from the Max Planck Institute of Molecular Physiology, Germany, have developed a method, TomoTwin, an open-source general picking model for cryogenic-electron tomograms. The method is based on deep metric learning and incorporates the embedding of tomograms in an information-rich, high-dimensional space that separates macromolecules according to their three-dimensional structures. The localization of particles within…

Read More Fast and Accurate Imaging of Proteins in Cells with TomoTwin: A Novel AI-based Software
AI | Bioinformatics | COVID-19 | Deep Learning | News | Paper Summary | Proteomics | SARS-CoV-2 | Trending

De Novo Protein Interaction Design from Protein Surface Fingerprints using a Geometric Deep Learning Model ‘MaSIF-seed’
BySipra Das May 1, 2023May 7, 2023

The molecular surface of a protein is represented in the form of geometric and chemical attributes that create the unique fingerprint for identifying protein interaction. Geometric deep-learning-based algorithms can be used to analyze these fingerprints, which can help researchers design new computational tools to study Protein interactions. Inferring protein-protein interactions (PPIs) solely from their structural…

Read More De Novo Protein Interaction Design from Protein Surface Fingerprints using a Geometric Deep Learning Model ‘MaSIF-seed’
Bioinformatics | Machine Learning | News | Paper Summary | Proteomics | Systems Biology | Trending

Bridging the Gap Between Proteomics and Systems Biology with ProInfer: A Machine Learning-based Approach for Protein Inference Analysis
BySipra Das April 27, 2023October 22, 2026

Protein identification has gained much importance over the last few years. In the shotgun proteomics-based approach, peptide fragments are used to identify proteins. The quantification of proteins from identified peptides is a difficult task. Scientists have suggested ProInfer, a new machine learning-based approach for performing Protein Inference based on biological networks. Mass Spectrometry (MS)-based Proteomics…

Read More Bridging the Gap Between Proteomics and Systems Biology with ProInfer: A Machine Learning-based Approach for Protein Inference Analysis
Bioinformatics | News | NGS | OMICS | Paper Summary | Proteomics | RNA-Seq | Trending

Researchers Introduce PALMO: A Novel Software Platform for Longitudinal Multi-omics Data Analysis
ByDiyan Jain April 5, 2023April 5, 2023

In the past few years, there has been a significant increase in multi-omics data generation for biomedical research. However, the analysis of these large-scale, complex, and heterogeneous datasets represents an enormous challenge for researchers. Recently, researchers from the Allen Institute of Immunology have developed a ground-breaking PALMO platform, which contains five analytical modules allowing the…

Read More Researchers Introduce PALMO: A Novel Software Platform for Longitudinal Multi-omics Data Analysis
AI | Bioinformatics | Deep Learning | News | Proteomics | Tools

Enzyme Function Prediction from Amino Acid Sequence: How AI is Leading the Way
ByDr. Tamanna Anwar April 4, 2023April 4, 2023

An innovative artificial intelligence program called CLEAN (contrastive learning–enabled enzyme annotation) has the ability to predict enzyme activities based on their amino acid sequences, even if the enzymes are unfamiliar or inadequately understood. The researchers have reported that CLEAN has surpassed the most advanced tools in terms of precision, consistency, and sensitivity. However, a deeper…

Read More Enzyme Function Prediction from Amino Acid Sequence: How AI is Leading the Way
AI | Bioinformatics | Machine Learning | News | Paper Summary | Proteomics | Trending

Pushing the Limits of Protein Detection: The Role of Machine Learning
ByBanhita Maitra March 16, 2023November 24, 2023

The detection of biomolecules at the nanoscale is of great significance in fundamental biology research, just as it is for biomedical investigations. The evolution of techniques for the detection and characterization of biomolecules has resulted in remarkable scale and resolution in terms of the size and mass of the molecules. Scientists from Germany have achieved…

Read More Pushing the Limits of Protein Detection: The Role of Machine Learning
AI | Antibiotic Resistance | Bioinformatics | Infectious Diseases | News | Paper Summary | Proteomics | Structural Biology | Trending

AI-Powered Structural Proteomics Unveils New Insights into Protein Complexes in Cells
BySejal Saxena March 13, 2023October 22, 2026

Molecular biology is being revolutionized by the application of artificial intelligence to simulate the structures of proteins and their complexes. Researchers utilized a combination of in-cell crosslinking mass spectroscopy and co-fractionation mass spectroscopy in order to find protein-protein interactions in Bacillus subtilis. With the help of AlphaFold-Multimer, the scientists predicted the structures of protein interactions,…

Read More AI-Powered Structural Proteomics Unveils New Insights into Protein Complexes in Cells
Bioinformatics | Metabolomics | News | Paper Summary | Proteomics | Tools | Trending

Scientists Introduce “MZmine3” for Processing Big Data to Identify Hidden Chemicals in Complex Mixtures
ByBanhita Maitra March 12, 2023March 12, 2023

Scientists from Prague have developed MZmine3, a scalable platform for the analysis of mass spectrometry (MS) data from different instrumental setups. The platform supports hybrid datasets from various setups such as liquid and gas chromatography (LC and GC)-MS, ion mobility spectrometry (IMS)-MS, and MS imaging. Spatial metabolomics analyses with increased annotation confidence is now feasible…

Read More Scientists Introduce “MZmine3” for Processing Big Data to Identify Hidden Chemicals in Complex Mixtures
Bioinformatics | Drug Discovery | Infectious Diseases | News | Proteomics | Structural Biology | Trending

The Fight Against Tuberculosis Takes a Major Step Forward: Scientists Find Flaws in Bacterium by Studying Ferredoxins
ByDr. Tamanna Anwar February 11, 2023October 22, 2026

Researchers from Skoltech, MIPT, the National Academy of Sciences of Belarus’ Institute of Bioorganic Chemistry (IBOCH NAS), and the Russian Academy of Sciences’ Institute of Biomedical Chemistry have studied the structures of ferredoxins from Mycobacterium tuberculosis and their complexes with interacting proteins. The study aims to discover new targets for anti-tuberculosis drug development by closely examining the…

Read More The Fight Against Tuberculosis Takes a Major Step Forward: Scientists Find Flaws in Bacterium by Studying Ferredoxins
Bioinformatics | News | Paper Summary | Proteomics | Trending

Generative Models for Peptide Design: Discovering Calcineurin Protein-protein Interactions Disruptors
BySejal Saxena February 9, 2023October 22, 2026

All organisms depend on protein-protein interactions (PPIs) for cellular and biological activities. This paper introduces a novel method for building peptide binders for “undruggable” protein-protein interactions. A machine learning approach generates different candidate peptides from natural binding regions from protein partners. Molecular docking and in-vitro microchip-based binding assays filter the peptides. The research confirms and…

Read More Generative Models for Peptide Design: Discovering Calcineurin Protein-protein Interactions Disruptors
Bioinformatics | News | OMICS | Paper Summary | Proteomics | Trending

In-depth Mapping of Protein Localizations in Whole Tissue Using Micro-scaffold Assisted Spatial Proteomics (MASP)
ByBanhita Maitra February 5, 2023February 5, 2023

Researchers from the Jun Qu lab at SUNY Buffalo, New York, have developed a revolutionary method for in-depth mapping of protein localization in whole tissue. The method implements the cutting-edge technique of micro-scaffold-assisted spatial proteomics (MASP). The daunting task of accurate, in-depth mapping of protein localizations at the whole-tissue level has been achieved by using…

Read More In-depth Mapping of Protein Localizations in Whole Tissue Using Micro-scaffold Assisted Spatial Proteomics (MASP)
Bioinformatics | Cancer Research | Drug Discovery | News | NGS | OMICS | Proteomics

New Hope in the Fight Against Cancer: Scientists Discover Nutrient that Cancer Cells Crave
ByDr. Tamanna Anwar February 4, 2023October 22, 2026

Cancer is one of the prominent causes of death globally, and discovering new methods to prevent and cure it is important for public health. Understanding the particular nutrients that cancer cells require is one of the strategies researchers are investigating to fight the disease. Arginine is one of the important amino acids produced by our…

Read More New Hope in the Fight Against Cancer: Scientists Discover Nutrient that Cancer Cells Crave
AI | Bioinformatics | Biomedical Engineering | Computational Models | Deep Learning | Drug Discovery | Machine Learning | News | Proteomics | Trending

AI Proteins: Unlocking the Potential of Protein Generation from Scratch with Natural Language Model “ProGen”
ByDr. Tamanna Anwar January 28, 2023October 22, 2026

Scientists from the University of California, San Francisco, have created an inventive AI system that can create entirely new enzymes from scratch. Even though the amino acid sequences of these synthetic enzymes differ significantly from those of any naturally occurring protein, they have demonstrated remarkable efficacy in laboratory experiments. In other words, using state-of-the-art technology,…

Read More AI Proteins: Unlocking the Potential of Protein Generation from Scratch with Natural Language Model “ProGen”
Antibiotic Resistance | Bioinformatics | Cancer Research | News | Paper Summary | Proteomics | Trending

Pancreatic Cancer and Drug Resistance: Researchers Identify Key Metabolic Regulators
ByCatherene Tomy December 16, 2022December 16, 2022

Drug resistance can be countered only by interrupting the adaptive measures taken by the cells to deflect the drug action. Scientists from the School of Pharmacy and Pharmaceutical Sciences, University of Buffalo, performed an extensive study through proteomic analysis that identified key regulators driving the resistance against Gemcitabine, the principal chemotherapeutic against Pancreatic Adenocarcinoma. The…

Read More Pancreatic Cancer and Drug Resistance: Researchers Identify Key Metabolic Regulators
Bioinformatics | Computational Models | Deep Learning | Machine Learning | News | Paper Summary | Proteomics | Trending

Meet AlphaPeptDeep: a Deep Learning Framework for Predicting Peptide Properties from Sequences
ByShwetha S November 28, 2022November 28, 2022

A research team led by Professor Matthias Mann from the Max Planck Institute of Biochemistry has developed AlphaPeptDeep. AlphaPeptDeep is a Python framework built on the PyTorch deep learning library that can learn and predict peptide properties. AlphaPeptDeep additionally includes a plug-in capability that allows non-experts to develop models with just a few lines of…

Read More Meet AlphaPeptDeep: a Deep Learning Framework for Predicting Peptide Properties from Sequences
Bioinformatics | Genetic Engineering | Metabolomics | News | Paper Summary | Proteomics | Tools | Transcriptomics | Trending

Scientists Introduce an Automated Pipeline ‘Galaxy-SynBioCAD’ for Synthetic Biology Design and Engineering
BySrishti Sharma September 6, 2022October 22, 2026

A toolshed for synthetic biology, metabolic engineering, and industrial biotechnology is available through the Galaxy-SynBioCAD portal. Using the tools and workflows available on the portal, one can create libraries of strains that produce the desired chemical targets, spanning a comprehensive metabolic pathway design and engineering process from selecting strains and targets, designing DNA parts to…

Read More Scientists Introduce an Automated Pipeline ‘Galaxy-SynBioCAD’ for Synthetic Biology Design and Engineering
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Tumor Treating Fields Against Glioblastoma: Identification of Potential Targets through Whole Transcriptome and Proteome Analyses
ByTanveen Kaur August 21, 2022October 22, 2026

Scientists from the Central South University, China, developed a novel Tumor Treating Fields ‘TTFields’ system named “CL-301A” and showcase its efficacy in the suppression of glioblastoma cell proliferation and induction of cell apoptosis. One of the most dangerous types of brain cancer is glioblastoma. The most recent method of treating glioblastoma (GBM) is called tumor…

Read More Tumor Treating Fields Against Glioblastoma: Identification of Potential Targets through Whole Transcriptome and Proteome Analyses

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