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Uncovering Tumour Heterogeneity: How Single-cell Technologies are Transforming Cancer Treatment and Drug Development
ByDeotima Chakraborty July 15, 2024October 22, 2026

Single-cell technologies are effective drug development and discovery tools, serving important functions at several phases. They aid in identifying potential therapeutic targets, streamline single-cell high-throughput screening, and support pharmacokinetic investigations of anti-tumor medications. New tools for single-cell research combine multiple molecular information, increase the size of data, and characterize the influence of genes on phenotypic…

Read More Uncovering Tumour Heterogeneity: How Single-cell Technologies are Transforming Cancer Treatment and Drug Development
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RNAfold: Leveraging Variational Autoencoders for Accurate RNA Tertiary Structure Prediction
ByAnshika Gupta June 26, 2024October 22, 2026

In drug development, the accurate prediction of RNA structures plays a pivotal role. Leveraging the power of machine learning, particularly Variational Autoencoders (VAEs), has emerged as a game-changer in this domain. Recent advancements by Quantori LLC, Cambridge, USA researchers have showcased the superiority of VAE models in RNA folding, surpassing traditional methods with remarkable precision….

Read More RNAfold: Leveraging Variational Autoencoders for Accurate RNA Tertiary Structure Prediction
AI | Algorithm | Bioinformatics | Health | LLM | Medical Informatics | News | Paper Summary | Trending

A New Era of AI in Medicine: Google’s Med-Gemini Sets New Standards
ByDeotima Chakraborty May 6, 2024October 22, 2026

AI faces significant obstacles in achieving excellence in a wide range of medical applications since it needs sophisticated reasoning, access to current medical information, and comprehension of complicated multimodal input. With their robust general abilities in multimodal and long-context reasoning, Gemini models present fascinating opportunities in medicine. Google researchers present Med-Gemini, a family of highly…

Read More A New Era of AI in Medicine: Google’s Med-Gemini Sets New Standards
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Meet MolProphet: A One-Stop AI Platform for the Early Stages of Drug Discovery
ByAnshika Gupta April 5, 2024October 22, 2026

Are you aware that plenty of operational AI applications have emerged in the early stages of small-molecule drug discovery? Do you recognize that those packages regularly require a thorough grasp of software programs and hardware, as well as a specialization in an optimistic effort, inflicting boundaries for regular users, in fact, normalization and switching among…

Read More Meet MolProphet: A One-Stop AI Platform for the Early Stages of Drug Discovery
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Eurofins Discovery Launches DiscoveryAI SAFIRE: A New AI Platform for Drug Discovery
ByDr. Tamanna Anwar March 3, 2024October 22, 2026

The drug discovery process is unduly time-consuming and expensive. Extensive laboratory testing is required to evaluate potential drug candidates for absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. Compounds that fail to meet acceptable thresholds for these properties may be unsafe or ineffective in humans, leading to high failure rates in clinical trials. But what if…

Read More Eurofins Discovery Launches DiscoveryAI SAFIRE: A New AI Platform for Drug Discovery
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CombFold: Advancing Structure Prediction of Large Protein Assemblies with Combinatorial Algorithms and AlphaFold2
ByDeotima Chakraborty February 9, 2024October 22, 2026

Deep learning models like RosettaFold and AlphaFold2 can predict protein structure with high accuracy; however, they still have difficulties when it comes to intricate connections between large proteins. To combat this problem, scientists from The Hebrew University of Jerusalem introduced CombFold, a hierarchical and combinatorial assembly technique that uses pairwise interactions between subunits predicted by…

Read More CombFold: Advancing Structure Prediction of Large Protein Assemblies with Combinatorial Algorithms and AlphaFold2
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Atomic AI’s ATOM-1: Leveraging Chemical Mapping Data to Optimize RNA Therapeutics
BySonal Keni December 20, 2023January 4, 2024

New avenues are being paved in the world of healthcare every day. One of the most promising new developments is the creation of RNA-based medications. Demonstrating great therapeutic potential, this new class of therapies offers novel ways of curing diseases. However, their full potential hasn’t yet been unlocked, largely due to a lack of understanding…

Read More Atomic AI’s ATOM-1: Leveraging Chemical Mapping Data to Optimize RNA Therapeutics
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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
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Empowering Medical Research with Drugst.One: A Seamless Plug-and-Play Approach for Online Systems Medicine and Network-Based Drug Repurposing
ByNeegar Naushaba Iqbal August 15, 2023October 22, 2026

Researchers from the University of Hamburg, Germany, in collaboration with researchers from Denmark, Canada, the USA, Spain, Slovakia, and Israel, have designed Drugst.One, a platform that transforms complex computational tools into user-friendly, web-based utilities for finding novel applications for existing drugs. With as little as three lines of code, Drugst.One can convert any gene or…

Read More Empowering Medical Research with Drugst.One: A Seamless Plug-and-Play Approach for Online Systems Medicine and Network-Based Drug Repurposing
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Meet Mapinsights: A New Toolkit for Impeccable Quality Control of High-Throughput Sequencing Data
ByNeegar Naushaba Iqbal July 14, 2023November 24, 2023

High-Throughput Sequencing (HTS) has drastically transformed the world of genomics by allowing rapid and accurate detection of genomic variations at the level of individual base pairs. However, the presence of technical artifacts (hidden non-random error patterns affecting the accuracy of variant identification) degrades HTS data quality. Scientists from the National Institute of Biomedical Genomics, India,…

Read More Meet Mapinsights: A New Toolkit for Impeccable Quality Control of High-Throughput Sequencing Data
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Meet OrthoVenn3: A Powerful, Web-based Platform for Analyzing and Visualizing Orthologous Data Across Genomes
BySipra Das May 5, 2023May 7, 2023

Recent developments in comparative genomics studies, along with the availability of cutting-edge computational tools, have revived the study of evolutionary biology and genetics in a new way. Existing computational tools can efficiently interpret orthologous clusters of genes and determine phylogenetic relationships among species. The recently upgraded release of the Web-based program OrthoVenn, called OrthoVenn3, with…

Read More Meet OrthoVenn3: A Powerful, Web-based Platform for Analyzing and Visualizing Orthologous Data Across Genomes
Algorithm | Bioinformatics | GWAS | Health | Medical Informatics | News | Paper Summary | Trending

Broad’s Scientist Introduce a Machine Learning Model to Identify Genetic Factors for Cardiovascular Diseases
BySipra Das May 3, 2023May 7, 2023

Using the heart as an investigational model, scientists at the Broad Institute of MIT and Harvard have designed an autoencoder-based machine-learning pipeline that can effectively predict a patient’s heart condition based on image data from ECGs and MRIs. The approach could also be used to detect markers related to cardiovascular diseases. Nearly all areas of…

Read More Broad’s Scientist Introduce a Machine Learning Model to Identify Genetic Factors for Cardiovascular Diseases
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Meet MitoTNT: A Novel Approach for Tracking Mitochondrial Temporal Network in 4D Live-cell Fluorescence Microscopy Data
BySipra Das April 29, 2023April 30, 2023

Advancements in fluorescence microscopy-based imaging techniques have made it possible for researchers to view and analyze mitochondrial networks in 4D. Researchers at UCSD have released a new software called MitoTNT that utilizes fluorescence microscopy data to track mitochondrial time-varying networks. The efficiency of mitochondrial network tracking depends on the quality of the image generated by…

Read More Meet MitoTNT: A Novel Approach for Tracking Mitochondrial Temporal Network in 4D Live-cell Fluorescence Microscopy Data
Algorithm | Bioinformatics | Covid-19 News | News | Paper Summary | Phylogenetic Analysis | SARS-CoV-2 | Tools | Trending

EMBL-EBI Researchers Develop a Phylogenetic Tool ‘MAPLE’ to Uncover Insights from Pandemic-scale Genome Data
BySipra Das April 15, 2023May 21, 2023

The rapid influx of large genomic data during the recent pandemic caused by COVID-19 constrained the researcher’s ability to analyze vast microbial genomes at once due to the lack of faster and more powerful tools. Researchers at EMBL-EBI have recently come forward with a robust bioinformatics tool MAPLE which efficiently reduces the size of bulky genomic data….

Read More EMBL-EBI Researchers Develop a Phylogenetic Tool ‘MAPLE’ to Uncover Insights from Pandemic-scale Genome Data
AI | Algorithm | Bioinformatics | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Trending

MIT’s DiffDock: A Breakthrough Diffusion Generative Model-based Approach for Molecular Docking
ByBanhita Maitra April 5, 2023April 6, 2023

Researchers at the Abdul Jameel Clinic for Machine Learning in Health, MIT, have developed a novel method, DiffDock, an accelerated drug discovery pipeline using a diffusion generative model (DGM)-based approach for molecular docking. One of the crucial processes involved in a drug design pipeline involves molecular docking, which predicts the binding structure of a ligand…

Read More MIT’s DiffDock: A Breakthrough Diffusion Generative Model-based Approach for Molecular Docking
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Precise Protein-Ligand-Binding Site Mapping with ‘SiteRadar’: A Graph Machine Learning Algorithm
BySejal Saxena April 2, 2023May 7, 2023

The identification of ligand-binding sites on the surface of a protein is a vital aspect of structure-based drug design. SiteRadar is a new algorithm for identifying ligand-binding sites on protein surfaces, which is important for structure-based drug design. It outperforms existing techniques, including machine learning algorithms, and can detect up to 74% of true ligand-binding…

Read More Precise Protein-Ligand-Binding Site Mapping with ‘SiteRadar’: A Graph Machine Learning Algorithm
Algorithm | Bioinformatics | Cancer Research | Deep Learning | News | Paper Summary | Trending

Evaluating the Efficacy of Deep Learning Algorithms for Predicting Drug Synergy in Cancer Treatment
BySejal Saxena March 30, 2023March 30, 2023

Cancer therapies often become ineffective due to the development of resistance in the tumor cells against the treatment. One potential strategy to overcome this resistance was treating the patients with a combination of drugs. Scientists conducted a study to improve cancer treatment by developing deep-learning models for drug synergy prediction. The models were designed to…

Read More Evaluating the Efficacy of Deep Learning Algorithms for Predicting Drug Synergy in Cancer Treatment
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NHGRI’s Verkko Algorithm: An Advancement in Genome Assembly with Notable Limitations
BySejal Saxena February 25, 2023February 24, 2023

Substantial progress has been made in assembling the first complete human genome sequence by the Telomere-to-Telomere consortium. However, complex repetitions in diploid genomes are still difficult to decode. Using lengthy, accurate reads and haplotype-specific markers, the Verkko pipeline is an automated method for assembling diploid genomes with high precision. The construction of pangenomes and chromosome-scale…

Read More NHGRI’s Verkko Algorithm: An Advancement in Genome Assembly with Notable Limitations
Algorithm | Bioinformatics | Genomics | GWAS | News | Paper Summary | Tools | Trending

Whole-Genome Population Genomics Made Easy with “PRAWNS”: A Comprehensive Tool for Multiple-genome Analysis
ByBanhita Maitra February 22, 2023February 22, 2023

Scientists from the University of Maryland have developed PRAWNS, a scalable and efficient tool for multi-genome analysis. With the unprecedented number of complete and nearly complete genomes being accessible, researchers interested in understanding the genomic basis of phenotypes, such as antibiotic resistance in bacteria, require computational tools capable of performing multiple genome comparisons efficiently. However,…

Read More Whole-Genome Population Genomics Made Easy with “PRAWNS”: A Comprehensive Tool for Multiple-genome Analysis
AI | Algorithm | Bioinformatics | Deep Learning | Disease Diagnosis | Health | News | Trending

Speech Analysis Meets Artificial Intelligence: The Promise of Deep Learning for Depression Detection
ByDr. Tamanna Anwar February 9, 2023February 9, 2023

Scientists at Jinhua Advanced Research Institute and Harbin University of Science and Technology have developed a deep-learning algorithm that can identify depression through speech. This algorithm was trained to recognize emotions in spoken language by looking at various pertinent traits. Millions of people all over the world go through depression, which is a common mental…

Read More Speech Analysis Meets Artificial Intelligence: The Promise of Deep Learning for Depression Detection
AI | Algorithm | COVID-19 | Database | Drug Discovery | Paper Summary

Expediating the Discovery of Super Tight-Binding Antibodies with an AI Model “RESP”
ByBanhita Maitra February 3, 2023February 3, 2023

Scientists from UCSD have devised an efficient AI-based pipeline, RESP, for identifying high-affinity antibodies. Typically, researchers would employ directed evolution to enable iterative mutagenesis and selection to identify and assess high-affinity antibodies. Existing methods employing deep learning techniques fail to provide statistical estimates for assessing reliable predictions. RESP, as a pipeline, implements an autoencoder model…

Read More Expediating the Discovery of Super Tight-Binding Antibodies with an AI Model “RESP”
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Meet AlphaFill: An AI Algorithm to Fill Missing Ligands and Cofactors in AlphaFold Models
BySejal Saxena February 2, 2023February 2, 2023

According to Levinthal’s paradox, each protein may adopt around 10300 distinct structures. We now know 3-D structures for about 98% of the human proteome thanks to DeepMind’s AI system, AlphaFold. However, AlphaFold has limitations, such as its inability to generate coordinates for tiny molecules and ligands that are critical to the protein’s activity. Researchers from…

Read More Meet AlphaFill: An AI Algorithm to Fill Missing Ligands and Cofactors in AlphaFold Models
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Meet “Espresso”: The Solution for Accurate Quantification of Transcript Isoforms in Error-Prone RNA-Seq Data
ByDr. Tamanna Anwar January 22, 2023January 22, 2023

The Children’s Hospital of Philadelphia (CHOP) scientists have created ESPRESSO, a new computational tool for analyzing RNA-seq data. ESPRESSO aims to improve the detection and quantification of transcript isoforms, which are variations of a gene that can serve different functions. ESPRESSO is particularly useful when dealing with long-read RNA-seq data, which can be prone to…

Read More Meet “Espresso”: The Solution for Accurate Quantification of Transcript Isoforms in Error-Prone RNA-Seq Data
AI | Algorithm | Bioinformatics | Cancer Research | Chronic Diseases | Deep Learning | Disease Diagnosis | Documentaries | Neural Network | News | Precision Medicine | Trending

Deep Learning and Radiomics: A Game-changer for Identifying Glioblastoma and Brain Metastases
ByDr. Tamanna Anwar January 20, 2023January 20, 2023

According to a recent study from Karl Landsteiner University of Health Sciences (KL Krems), using radiomics and deep learning algorithms can quickly and accurately distinguish between glioblastoma (primary tumors) and brain metastases. The study, which was published in Metabolites, discovered that magnetic resonance-based radiological data of tumor oxygen metabolism provide a solid foundation for discrimination via…

Read More Deep Learning and Radiomics: A Game-changer for Identifying Glioblastoma and Brain Metastases
Algorithm | Bioinformatics | Biomedical Engineering | Cancer Research | Drug Discovery | Featured | Genomics | News | OMICS | Sequencing | Structural Biology | Tools | Trending

Top 10 Bioinformatics Breakthroughs of 2022!
ByCatherene Tomy December 27, 2022January 11, 2023

The field of bioinformatics has seen numerous exciting breakthroughs in the year 2022 that have transformed the landscape of biological research. Many important discoveries have advanced our understanding of complex biological processes and have led to new treatments and therapies for diseases. In this article, we will explore the top 10 bioinformatics discoveries of the…

Read More Top 10 Bioinformatics Breakthroughs of 2022!
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AI-Powered Dementia Detection: A Digital Solution for Identifying Undiagnosed Cases
ByDr. Tamanna Anwar December 24, 2022December 24, 2022

Scientists from the Regenstrief Institute, IUPUI, Indiana University, and the University of Miami are using Artificial Intelligence to identify undiagnosed cases of dementia in primary care settings as part of the Digital Detection of Dementia (D3) study. The study aimed to improve the timely diagnosis of dementia and provide diagnostic services to those who have…

Read More AI-Powered Dementia Detection: A Digital Solution for Identifying Undiagnosed Cases
Algorithm | Bioinformatics | Drug Discovery | News | Paper Summary | Trending

DrugRepo: A Scoring Algorithm for Drug Repurposing Incorporating Chemical and Genomic Features
ByCatherene Tomy December 12, 2022December 13, 2022

Scientists from the University of Helsinki, Finland, developed a drug repurposing scoring algorithm, DrugRepo, that predicted 6229 new drug-disease relationships across 545 diseases for 516 approved drugs. The effectiveness of the algorithm was validated through evaluation studies that identified ≥0.4 as an appropriate threshold for discovering new candidate drugs. The study is also accompanied by…

Read More DrugRepo: A Scoring Algorithm for Drug Repurposing Incorporating Chemical and Genomic Features
AI | Algorithm | Bioinformatics | Chronic Diseases | Health | News | Trending

Smartwatch ECG Signals Transformed into Diagnostic Tools for Heart Failure using Artificial Intelligence
ByDr. Tamanna Anwar November 20, 2022November 23, 2022

A new study published by researchers at the Mayo Clinic has shown that a smartwatch ECG can accurately detect heart failure in nonclinical environments. This is a significant breakthrough because it shows that heart failure can now be detected earlier and more effectively. The research published in Nature Medicine reports a couple of health technology…

Read More Smartwatch ECG Signals Transformed into Diagnostic Tools for Heart Failure using Artificial Intelligence
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Meet Deep-SMOLM: A Machine Learning Algorithm for Generating 5D Images of Proteins
ByShwetha S November 8, 2022November 7, 2022

Deep-SMOLM is a deep-learning-based estimator created by Washington University in St. Louis researchers that blends machine learning, physical laws, and biological principles. At a rate ten times quicker than iterative estimators, Deep-SMOLM correctly and precisely reconstructs 5D information of simulated biological fibers and experimental amyloid fibrils from images, including highly overlapping single molecule structures. A…

Read More Meet Deep-SMOLM: A Machine Learning Algorithm for Generating 5D Images of Proteins
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Kyoto University Scientists Integrated Probability Algorithms within a Pocket-sized Sequencing Device to Read RNA Modifications More Precisely
ByDr. Tamanna Anwar August 28, 2022August 28, 2022

Scientists at Kyoto University introduced two new approaches that could help better distinguish RNA modifications affecting how genetic code is read using sequencing technology. The researchers are getting closer to identifying RNA sequence changes that affect protein formation and can cause diseases. The method, which was published in the journal Genomics, combines probability algorithms with…

Read More Kyoto University Scientists Integrated Probability Algorithms within a Pocket-sized Sequencing Device to Read RNA Modifications More Precisely
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DeepBacs: A Deep Learning Approach to Analyze Bacterial Microscopy Images
BySrishti Sharma August 2, 2022August 2, 2022

Scientists from University College London demonstrate the use of various cutting-edge artificial neural networks to analyze images of bacterial microscopy. The approach will help future researchers to explore the prospective deep learning (DL) applications and employ pre-trained models in their research on a designated platform. Microbiology, the study of microorganisms and their community, is a…

Read More DeepBacs: A Deep Learning Approach to Analyze Bacterial Microscopy Images
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Deepmind’s AlphaFold Predicted the Structures of all the Proteins Known to Science, Expanding the AlphaFold DB by Over 200x
ByDr. Tamanna Anwar July 30, 2022October 22, 2026

The AlphaFold Protein Structure Database, created by DeepMind and EMBL’s European Bioinformatics Institute (EMBL-EBI), makes AI-enabled predictions of the 3D structures of nearly all cataloged proteins available to the scientific community for free and without restrictions. It has been a year since AlphaFold was made available for free worldwide distribution and AlphaFold Protein Structure Database…

Read More Deepmind’s AlphaFold Predicted the Structures of all the Proteins Known to Science, Expanding the AlphaFold DB by Over 200x
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Scientists Develop Digital Pathology Models without Human Intervention by Integrating Clinical Healthcare Data with AI
ByTanveen Kaur July 29, 2022November 11, 2022

Scientists unleash the potential of digital pathology data by training computer-aided diagnosis models and making use of convolutional neural networks without human annotations. The cancer diagnostics model developed in the study for empowering digital pathology limits the human effort to a minimum. Deep learning algorithms’ improved performance and the digitization of healthcare operations are opening…

Read More Scientists Develop Digital Pathology Models without Human Intervention by Integrating Clinical Healthcare Data with AI
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Novel ‘Fuzzy’ AI Algorithms to Help Patients with Memory Loss
ByDr. Tamanna Anwar July 18, 2022July 18, 2022

Like our brains, a new computer program created by Parham Aarabi of the University of Toronto can store and retrieve information strategically. An experimental tool that uses the novel algorithm to aid those with memory loss has also been developed by the associate professor in the Faculty of Applied Science & Engineering’s Edward S. Rogers…

Read More Novel ‘Fuzzy’ AI Algorithms to Help Patients with Memory Loss
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A Geometric Deep-Learning Model ‘EquiBind’ the Fastest Computational Molecular Docking Model
ByTanveen Kaur July 17, 2022October 22, 2026

MIT researchers have developed a geometric deep-learning model, EquiBind, which is 1,200 times faster than one of the fastest computational molecular docking models currently in use, QuickVina2-W, for effective binding of drug-like substances to proteins. One of the main challenges in drug discovery is to predict the binding properties of a drug-like chemical to a…

Read More A Geometric Deep-Learning Model ‘EquiBind’ the Fastest Computational Molecular Docking Model
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TranSalNet – AI System that Simulates Human Vision Holds Potential Application in Cancer Detection
ByDr. Tamanna Anwar July 5, 2022December 28, 2022

Scientists at Cardiff University have developed a state-of-the-art artificial intelligence (AI) system, ‘TranSalNet,’ which precisely anticipates the regions of an image where a person is most likely to gaze. The researchers claim that the unique method more accurately simulates human vision than any previous system based on human brain mechanics and its ability to discriminate…

Read More TranSalNet – AI System that Simulates Human Vision Holds Potential Application in Cancer Detection
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Scientists Develop a Novel GPU-based Machine Learning Model to Discover Human Brain Connectivity
ByDr. Tamanna Anwar June 30, 2022July 1, 2022

Indian Institute of Science (IISc) researchers have created a novel GPU-based machine learning model to better understand and predict human brain connections across various brain regions. The researchers present “Regularized, Accelerated, Linear Fascicle Evaluation (ReAl-LiFE)”, a GPU-based execution of a state-of-the-art streamline pruning algorithm (LiFE), which achieves >100× speedups over previous CPU-based implementations. The ReAl-LiFE…

Read More Scientists Develop a Novel GPU-based Machine Learning Model to Discover Human Brain Connectivity
AI | Algorithm | Bioinformatics | Deep Learning | Health | Machine Learning | News | Paper Summary | Tools

Scientists Develop a Machine Learning Algorithm that uses Electronic Health Records to Predict Mental Health Crisis
ByTanveen Kaur May 23, 2022December 28, 2022

Scientists from Koa Health and Birmingham and Solihull Mental Health NHS Foundation Trust developed a machine learning model that uses electronic health records to detect the risk of a mental health crisis in patients over 28 days. The machine-learning algorithm continuously monitors patients for the possibility of a mental health crisis using anonymized electronic health…

Read More Scientists Develop a Machine Learning Algorithm that uses Electronic Health Records to Predict Mental Health Crisis
Algorithm | Bioinformatics | Genomics | Machine Learning | News | NGS | Sequencing | Tools | Trending

‘BWA-MEME’ – Machine Learning-Based Short Read Alignment Algorithm to Speed up DNA Sequencing
ByDr. Tamanna Anwar May 21, 2022June 18, 2022

The algorithm is the first full-fledged machine learning-based short read alignment algorithm to speed up DNA sequencing, that efficiently uses learned indices to solve the exact match search issue for efficient seeding. The human genome is made up of a whole set of DNA that is around 6.4 billion letters long. Reading the entire genome…

Read More ‘BWA-MEME’ – Machine Learning-Based Short Read Alignment Algorithm to Speed up DNA Sequencing
AI | Algorithm | AMR Alert | Chemoinformatics | Drug Discovery | Health | News

Artificial Intelligence Based ‘Waste-to-Valuable’ Algorithm for Repurposing Chemical Wastes into Useful Drugs
ByDr. Tamanna Anwar May 7, 2022October 22, 2026

The widespread use of computational waste-to-value algorithms can speed up the productive reuse of chemicals that would otherwise incur storage or disposal expenses or even pose environmental risks. Scientists from the Ulsan Institute of Science and Technology, Republic of Korea, have developed an innovative strategy to repurpose waste chemicals into usable products using artificial intelligence…

Read More Artificial Intelligence Based ‘Waste-to-Valuable’ Algorithm for Repurposing Chemical Wastes into Useful Drugs
Algorithm | Bioinformatics | Cancer Research | Machine Learning | News | Paper Summary | RNA-Seq | Trending

Scientists Discover a Sensitive Blood Test to Determine if a Pre-Cancerous Condition is Progressing to Malignancy
ByTanveen Kaur April 29, 2022November 9, 2022

A test developed by OHSU researchers could help doctors treat cancer earlier when it’s more likely to be cured. Scientists discover plasma cell-free RNA profiling, which distinguishes cancers from premalignant conditions in solid and hematological malignancies. They developed a blood test to determine if a pre-cancerous condition is progressing to malignancy, potentially allowing therapy early…

Read More Scientists Discover a Sensitive Blood Test to Determine if a Pre-Cancerous Condition is Progressing to Malignancy
Algorithm | Bioinformatics | Cell | Computational Models | Deep Learning | Machine Learning | News | OMICS | Paper Summary | Tools

DGCyTOF: Deep Learning with Graphic Cluster Visualisation Model for Predicting Cell Types from Single-Cell Mass Cytometry Data
ByTanveen Kaur April 16, 2022November 9, 2022

Researchers from The Ohio State University utilized deep-learning classification and hierarchical stable-clustering approaches to predict cell types from single-cell mass cytometry data. The DGCyTOF approach could facilitate the analysis of single-cell RNASeq data and other omics data. Single-cell mass cytometry, also called cytometry by time of flight (CyTOF), is a powerful high-throughput technology that permits…

Read More DGCyTOF: Deep Learning with Graphic Cluster Visualisation Model for Predicting Cell Types from Single-Cell Mass Cytometry Data
Algorithm | Bioinformatics | Health | News | Trending

Scientists Developed an Algorithm for Biometric Identification of People By their Heartbeat
ByDr. Tamanna Anwar March 26, 2022June 18, 2022

According to a study undertaken by the Universidad Carlos III de Madrid (UC3M) and the Shahid Rajaee Teacher Training University of Iran, the heartbeat can be utilized as a biometric approach to identify people. Biometrics is an area of science that studies how to identify persons and animals using biological or physical traits such as…

Read More Scientists Developed an Algorithm for Biometric Identification of People By their Heartbeat

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Algorithm

Expediating the Discovery of Super Tight-Binding Antibodies with an AI Model “RESP”

A Geometric Deep-Learning Model ‘EquiBind’ the Fastest Computational Molecular Docking Model

Scientists Develop a Machine Learning Algorithm that uses Electronic Health Records to Predict Mental Health Crisis

Artificial Intelligence Based ‘Waste-to-Valuable’ Algorithm for Repurposing Chemical Wastes into Useful Drugs

DGCyTOF: Deep Learning with Graphic Cluster Visualisation Model for Predicting Cell Types from Single-Cell Mass Cytometry Data

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