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New Modeling Tool Allows Microbiome Researchers to Map Community Ecology to Ecosystem Function
A promising new open-source metabolic modeling tool provides microbiome researchers a path forward in predicting ecosystem function from community structure. News of the software package, called MICOM, was developed in part by researchers in ISB’s Gibbons Lab, and its uses were published in the journal mSystems.
How Old Are You? Your Body Might Disagree With That Answer
Researchers at ISB harnessed deep molecular and physiological information to determine an individual’s biological age, which they found was reflective of overall health compared to chronological age. The findings were published in the Journals of Gerontology: Series A.
Malaria Researchers’ Findings May Have Implications for Preventing Spread of Deadly Disease
ISB researchers and their collaborators are using systems biology approaches to learn how the malaria parasite is able to transfer to humans via the bite of an infected mosquito. The information they have uncovered may help identify new ways to prevent people from contracting the deadly disease.
New Method to Detect, Analyze Rare T Cells Another Step Toward Personalized Cancer Vaccines
Members of ISB’s Heath Lab and their collaborators have developed a way to sensitively detect and analyze neoantigen-specific T-cell populations from tumors and blood. This promising development may have implications for creating targeted, individual-specific cancer vaccines.
Using Blood to Predict Gut Microbiome Diversity
Predicting the alpha diversity of an individual’s gut microbiome is possible by examining metabolites in the blood. The robust relationship between host metabolome and gut microbiome diversity opens the door for a fast, cheap and reliable blood test to identify individuals with low gut diversity.
New Diagnostic Method Predicts Therapy Response in Lung Cancer Patients
By using single-cell analysis to measure metabolic activities in rare disseminated tumor cells taken from non-small cell lung cancer (NSCLC) patients, ISB researchers and their collaborators can accurately predict how patients will respond to various cancer therapies, and how treatments will impact a patient’s physiological performance and survival.
Profiling Pathogen Gene Expression from Infected Host Cells
Researchers at ISB reported a novel method, Path-seq, to profile expression of all MTB genes within infected mice. This study presents the most comprehensive transcriptome profiling of MTB from in vivo infection and a major technical advancement for studying any host-pathogen interaction.
Reconstructing 'Ötzi' the Iceman’s last meal
Members of the Moritz lab, as part of an international consortium centered in Bolzano Italy, reports this week in Cell, “Current Biology”, a multi-omic approach to identify the stomach contents and microbiome of the 5300 year old Mummy, Oetzi, the Iceman from the Oetzal Alps on the Austrian/Italian border.
‘Pushing Cancer Research Forward:’ Powerful ISB Cancer Genomics Cloud Tool in Spotlight
Institute for Systems Biology, Google and CSRA have jointly created a cloud-based platform that allows researchers to quickly, reliably and securely access massive amounts of data in ways that, until now, haven’t been possible.
ISB Artwork Featured On Cover of Nature Biotechnology
Institute for Systems Biology and Arivale “Pioneer 100 Study” is featured on the cover of August’s Nature Biotechnology. The artwork was created by ISB’s Associate Director of Communications Allison Kudla in collaboration with contributing author John C. Earls, software engineer in Hood/Price Lab.
The Other Malaria: Finding New Targets for a Vaccine Against Plasmodium vivax
A new report in PLOS Neglected Tropical Diseases describes the results of an international collaboration led by researchers at ISB and Seattle’s Center for Infectious Disease Research (CIDResearch). We used mass spectrometry-based proteomics to identify nearly 2,000 proteins present in Plasmodium vivax parasites, one of the Plasmodium species that cause the disease malaria in humans. The work was done on parasites dissected from mosquito salivary glands, parasites that were in…
New Study on How Microbes Learn to Predict the Future
In a study published in Genome Biology and Evolution, researchers at Institute for Systems Biology (ISB) designed an experiment to evolve novel adaptive prediction capability in yeast by repetitively exposing it to caffeine, followed by a toxin. Remarkably, the yeast cells learned the structure of this novel environmental pattern within as few as 50 generations to use caffeine as a cue for anticipating and mitigating lethal effects of the toxin.
Institute for Systems Biology and Arivale “Pioneer 100 Study” Establishes Foundation for New Industry of Scientific Wellness
Institute for Systems Biology and Arivale “Pioneer 100 Study” Establishes Foundation for New Industry of Scientific Wellness. Personal, dense, dynamic data clouds enable novel insights into mechanisms of wellness and disease, new approaches to biomarker discovery, and the empowerment of individuals to enhance their own health.
TCGA, ISB Researchers Identify Potential Drug Targets for Leading Form of Deadly Liver Cancer
June 19, 2017 Researchers in ISB’s Shmulevich Lab and their colleagues in The Cancer Genome Atlas Research Network performed the first large-scale, multi-platform analysis of hepatocellular carcinoma, the predominant form of liver cancer. Study was published on June 15, 2017, in the journal Cell. 3 Bullets: Liver cancer is the second most common cause of death from cancer worldwide. ISB researchers and colleagues from The Cancer Genome Atlas Research Network…
New Publication in Cell Systems
April 25, 2017 A Cell-Surface Membrane Protein Signature for Glioblastoma 3 bullets: Using integrated protein and gene expression data, ISB researchers developed a 33-gene signature for glioblastoma, an aggressive form of brain cancer. Glioblastoma gene signatures are associated with TGF-b signaling and cancer invasion. Researchers think that some of the glioblastoma gene signatures have the potential to be used as blood biomarkers for this aggressive cancer. Read the full summary…
Former Undergrad Intern Publishes Algorithm in PLOS Computational Biology
Posted March 1, 2017 In a study published in PLoS Computational Biology, researchers at Institute for Systems Biology (ISB) have developed a multiscale mutation clustering algorithm (M2C) that identifies variable length regions with high mutation density in cancer genes. The M2C algorithm was developed by William Poole (first author on the paper), who started as a summer intern in 2013 as part of ISB’s Center for Systems Biology internship program….