Cancer research through a bioinformatics lens: genomic profiling, biomarkers, tumor biology and computational oncology.
The researchers at the Department of Energy’s Oak Ridge National Laboratory have convincingly connected the function of a specific domain of proteins vital in plant-microbe biology to a cancer trigger in humans, the knowledge that had puzzled scientists for decades. The research findings were reported in Nature Communications Biology, which provides a new route for creating…
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…
Baylor College of Medicine researchers introduce a new sequencing technique ‘NT-seq’ for simultaneously mapping all three forms of DNA methylation. All known methylation motifs in Escherichia coli and Helicobacter pylori genomes were reliably detected by NT-seq, which may also be utilized to find de novo methylation motifs. NT-seq offers a quick and effective way for genome-wide mapping of different…
Scientists from the Korea Advanced Institute of Science and Technology propose the PICASSO technique, which enables more than 15-color imaging of spatially overlapping proteins in a single imaging round without using any reference emission spectra. For a wide spectrum of researchers, the PICASSO technique offers a multiplexed imaging tool with great accessibility and accuracy. According…
A research team from Nagoya University in Japan has created a 3-Dimensional computational simulation of the formation of the genome structure in the human cell nucleus. The model is expected to help in understanding cellular regulatory mechanisms and diseases like cancer that modify DNA. Because it influences DNA reading and replication, the three-dimensional shape of…
Scientists from the Technical University of Denmark (DTU) and the University of California San Diego present a systems biology workflow that integrates genome mining with a detailed pangenome analysis for detecting genes associated with a particular biosynthetic gene clusters (BGCs). The study will help find novel secondary metabolites, comprehend their physiological functions better, and find…
Scientists at the Francis Crick Institute have uncovered how the DNA double helix structure is opened to allow DNA replication. The research could pave the way for additional investigations to understand this mechanism better, particularly how it can go wrong in conditions like cancer. Scientists have struggled to comprehend how the two strands of DNA…
The algorithms that track users’ Netflix viewing habits could soon be used to track cancer development in order to direct doctors in managing cancer. An international team of researchers led by Dr. Nischalan Pillay (UCL Cancer Institute) and Dr. Ludmil Alexandrov (University of California, San Diego) used AI to identify 21 frequent faults in the…
According to new research headed by University College London experts existing drugs that affect the impact of the hormone progesterone, such as mifepristone, have been found to reduce the risk of severe triple negative breast cancer in women with a BRCA1 gene mutation. In premenopausal women, breast cancer is the main cause of death. Progesterone…
Scientists used hematoxylin and eosin (H&E) images with a deep learning approach to predict disease outcomes, an emerging technique for the improvement of clinical trials via computational methodology. For treatment choices and disease outcome monitoring, it is highly clinically relevant to understand the variables that affect a cancer patient’s prognosis. The use of whole slide images…
Scientists have developed ERX-41, a potent therapeutic drug with a well-defined molecular target (Lysosomal Acid Lipase, LAL) and mechanism of action (disruption of protein folding and production of ER stress) that could be useful in the treatment of patients with multiple solid cancers (Hard to Treat Cancers). Scientists from the University of Texas, Dallas synthesized…
Scientists at Tokyo Tech have produced computational DNA droplets that can recognize specific patterns in tumor biomarker microRNA sequences by merging the technologies of DNA droplets and DNA computing. When integrated into biomolecular robots and artificial cells, the technology will have potential applications in cancer diagnosis, drug resistance analysis, and residual tumor detection. DNA droplets…
A team led by the University of Maryland utilizes machine learning to explain why a “wonder drug” may not work in all patients. Understanding how mutations cause a medicine to become ineffective is a huge issue. The mechanism by which mutations produce drug resistance is frequently discussed solely in terms of thermodynamics. The case where…
Scientists from Akademi University, Turku, Finland, and Pasteur Institute, Paris, France have developed a new software TrackMate v7 that may allow tracking things in photos. The technology, which is based on artificial intelligence, will serve as a catalyst for future discoveries in the biological sciences. Object tracking, or following objects across time, is a critical…
Scientists from Cold Spring Harbor Laboratory (CSHL) have discovered a key process which shows how protein production is regulated to keep the cells healthy. Scientists believe that this mechanism is common in many different species and that it could one day aid in the creation of new microRNA-based medical therapeutics. Proteins are made in cells…
PGDx Elio tissue complete, which the FDA has approved for the analysis of 505 cancer-related genes, will enable the development of more effective precision oncology treatment options. The researchers from Personal Genome Diagnostics Inc. (PGDx) explain the developmental and analytical validation processes of the PGDx elio tissue complete test. It is an automated NGS-based approach…
Scientists from the University of Minnesota, Minneapolis, USA, with their collaborators, developed a machine learning framework for a multi-omic integration to identify the shared and disease-specific host gene microbiome associations across human diseases. They identified the associations between gut microorganisms and host genes that portray shared as well as disease explicit patterns. While gut microbiome…
CancerVar leverages machine learning frameworks to evaluate the potential relevance of somatic cancer mutations in terms of cancer diagnosis, prognosis, and targetability, in addition to simply discovering them. Researchers at Children’s Hospital of Philadelphia (CHOP) developed CancerVar, a novel machine learning empowered tool to interpret somatic variants in cancer. CancerVar can be accessed either as…
Top 10 Applications of Artificial Intelligence in Healthcare in 2022 and Beyond The healthcare industry has always been one of the leaders in using technology to make lives better and more efficient. Artificial intelligence (AI) in healthcare has started to enter the market, but it’s not just used as an additional tool — it’s transforming…
Microscopic imagers may be used in oncology to track and observe cell motions and dynamics, indicating tissues’ real-time response to therapy. Scientists from the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, reconstruct cellular images in 3D from microfabricated imagers using fully-adaptive deep neural networks. This research is the first work that…
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…
Consultation with a machine learning tool helped providers determine more accurately whether patients had a complete response to chemotherapy. Scientists from the University of Michigan investigated the impact of a computerized artificial intelligence (AI)-based decision support system (CDSS-T) on physicians’ diagnostic accuracy in measuring bladder cancer treatment response. The CDSS-T has the potential to increase…
Scientists at Georgetown Lombardi Comprehensive Cancer Center have uncovered genetics and other characteristics that can predict if a woman is at risk of breast cancer recurrence, opening up new research possibilities for preventing a new tumor from growing. The discovery was made possible by Georgetown Lombardi’s sophisticated technology, which allows laboratory researchers to expand dramatically…
The scientists from Unidad de Investigación Biomédica en Cáncer, México, looked at numerous facets of prostate cancer, including new molecular markers linked to diagnosis, prognosis, therapy prediction, and how bioinformatics tools like machine learning and deep learning can help in the clinic. The findings are expected to improve prostate cancer patient clinical care by applying…
Scientists from the University of Cambridge have used a medley of automated text analysis and the ‘robot scientist – Eve’ to semi-automate the procedure of reproducing research results. The lack of reproducibility is one of the biggest crises facing modern science. Scientific findings should be not only ‘replicable’ (i.e., reproducible in the same lab under…
A team of scientists led by Prof. YE Mingliang from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences (CAS) has recently created Glyco-Decipher, a new glycoproteomics software tool for the sensitive interpretation of N-glycopeptide mass spectra with high confidence. Glyco-Decipher is a promising method for enhancing glycoproteomics analysis in biological…
To estimate cell-to-cell heterogeneity in non-Markovian signaling systems, mathematicians from The Korea Advanced Institute of Science and Technology (KAIST) and Institute for Basic Science (IBS), Korea, devised a Bayesian inference approach. The approach could aid in the development of treatments that kill pathogenic or cancerous cells. Recognizing the source of cell-to-cell variability in cell signaling…
Scientists from the National Cancer Institute, Bethesda, and the University of Maryland have developed a computational tool to determine gene-target combinations for personalized cancer therapies. The tool has the potential to aid in the creation of novel combinatorial treatments for cancer patients. For mining a vast cohort of single-cell transcriptomics information, the scientists utilize combinatorial…
In a report published in Nature Communications, researchers from the Department of Oncology-Pathology at Karolinska Institutet, Sweden established a cell line resource dataset and analysis tool ‘Functional Omics Resource of ALL (FORALL)’ that could be used to uncover the features that make specific leukemias vulnerable to new forms of targeted medicines. The researchers used proteomics,…
Preimplantation genetic testing (PGT) of embryos fertilized in-vitro has been proposed as a strategy to diminish transmission of common diseases; in any case, a more comprehensive embryo genetic assessment, joining the impacts of common variants and rare variants, stays inaccessible. In this study, the scientists used molecular and statistical techniques to infer inherited genome sequence…
‘CellTrek’ can accurately map single cells in diverse tissue types to resolve their spatial organization. The tool identifies the location of particular cell types to drive biological insights. Scientists at The University of Texas MD Anderson Cancer Center have created a new computational methodology that successfully combines data from simultaneous gene-expression profiling approaches to build…
Crislyn D’Souza-Schorey, the Morris Pollard Professor in the Department of Biological Sciences, and collaborators discovered that DNA “cargo” is transported in tiny informational sacs called extracellular microvesicles in their most recent study, which was published in Cell Reports. Their research is a continuation of work done in her lab to understand better how cells share…
Stanford University researchers have created a graph-based algorithm for reconstructing interactomes and identifying clinically important cell-cell interactions. The algorithm can be used to create a global network of cell-to-cell cross-talk. REMI is a modernized, novel algorithm that utilizes graph-based ways to deal with creating a global cell-cell interaction network by assessing the conditional dependency of…
The researchers from Curtin University, Australia, and the University of Western Australia developed a system to carry out the complete process of directed evolution in silico. Thanks to revolutionary software that mimics evolution, the building blocks of life-saving treatments might be produced in days rather than years. According to the research published this week in…
The researchers at the Mayo Clinic Cancer Center in Florida, in a recent study published in Nature Communications, validate the use of genetic sequencing to predict whether patients with gastric cancer would benefit from chemotherapy or immunotherapy. Gastric cancer is one of the significant reasons for cancer-related deaths worldwide. Most patients with gastric cancer receive…
Scientists from MIT probed into how proteins recognize and bind to one another, informing drug treatments for cancer. A single cell, despite its small size, has billions of molecules that buzz around and bond to one another, performing critical tasks. About 20,000 proteins are encoded in the human genome, the majority of which interact with…
Scientists from the York University, Toronto, Canada, investigated a novel deep learning-based methodology to predict breast cancer response to neo-adjuvant chemotherapy (NAC) using the quantitative ultrasound (QUS) multiparametric imaging at pre-treatment. Breast cancer is the most general type of cancer in women and the leading cause of cancer-related death. Locally advanced breast cancer (LABC) is…
A low-cost metagenome sequencing technology has been developed by scientists from the Chinese Academy of Sciences’ Qingdao Institute of Bioenergy and Bioprocess Technology (QIBEBT). It allows high-resolution disclosure of a microbiome’s whole ‘landscape’ of species, even from low-biomass, damaged, or polluted samples. The ‘microbiome‘ is referred to a community of microorganisms (bacteria, fungi, protists, and…
Researchers from Harvard’s Wyss Institute, Harvard Medical School, and the ETH Zurich have predicted and validated genetic safe harbors for therapeutic genes, making gene and cell treatments safer, more efficient, more predictable. According to the researchers, “genomic safe harbors (GSHs)” could enhance the efficacy, persistence, and predictability of future gene and cell therapies that are…
Scientists from the Broad Institute of MIT and Harvard discovered an approach to studying the functional implications of the millions of mutations linked to cancer by pooling Perturb-seq and measuring the impact of TP53 and KRAS variants on RNA profiles in single cancer cells. Precision medicine entails predicting how specific genetic variants affect a patient’s…
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