ORCID Profile
0000-0002-1708-8454
Current Organisation
University of California, San Diego
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Publisher: Royal Society of Chemistry (RSC)
Date: 2018
DOI: 10.1039/C8CC90189A
Abstract: For the third time, a Faraday Discussion addressed ionic liquids. Encompassing the wealth of research in this field, the contributions ranged from fundamental insights to the erse applications of ionic liquids. Lively discussions initiated in the lecture hall and during poster sessions then seamlessly continued during the social program.
Publisher: American Chemical Society (ACS)
Date: 20-10-2015
Publisher: Springer Science and Business Media LLC
Date: 09-05-2022
Publisher: Springer Science and Business Media LLC
Date: 2010
Publisher: American Association for the Advancement of Science (AAAS)
Date: 17-06-2019
Abstract: An epistasis map (E-MAP) was constructed in the fission yeast, Schizosaccharomyces pombe , by systematically measuring the phenotypes associated with pairs of mutations. This high-density, quantitative genetic interaction map focused on various aspects of chromosome function, including transcription regulation and DNA repair/replication. The E-MAP uncovered a previously unidentified component of the RNA interference (RNAi) machinery ( rsh1 ) and linked the RNAi pathway to several other biological processes. Comparison of the S. pombe E-MAP to an analogous genetic map from the budding yeast revealed that, whereas negative interactions were conserved between genes involved in similar biological processes, positive interactions and overall genetic profiles between pairs of genes coding for physically associated proteins were even more conserved. Hence, conservation occurs at the level of the functional module (protein complex), but the genetic cross talk between modules can differ substantially.
Publisher: Elsevier BV
Date: 03-2010
Publisher: Cold Spring Harbor Laboratory
Date: 22-03-2020
DOI: 10.1101/2020.03.22.002386
Abstract: An outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption 1,2 . There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 04-12-2020
Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is closely related to the deadly coronaviruses SARS-CoV-1 and Middle East respiratory syndrome coronavirus (MERS-CoV). Considerable efforts are focused on developing treatments, and therapies that work across coronaviruses would be particularly valuable. Shedding light on the host factors hijacked by the viruses, Gordon et al. mapped the interactions between viral and human proteins for SARS-CoV-2, SARS-CoV-1, and MERS-CoV analyzed the localization of viral proteins in human cells and used genetic screening to identify host factors that either enhance or inhibit viral infection. For a subset of the interactions essential for the virus life cycle, the authors determined the cryo–electron microscopy structures and mined patient data to understand how targeting host factors may be relevant to clinical outcomes. Science , this issue p. eabe9403
Publisher: Springer Science and Business Media LLC
Date: 30-04-2010
Publisher: Proceedings of the National Academy of Sciences
Date: 26-02-2008
Abstract: Duplication of genes encoding transcription factors plays an essential role in driving phenotypic variation. Because regulation can occur at multiple levels, it is often difficult to discern how each duplicated factor achieves its regulatory specificity. In these cases, a “systems approach” may distinguish the role of each factor by integrating complementary large-scale measurements of the regulatory network. To explore such an approach, we integrate growth phenotypes, promoter binding profiles, and gene expression patterns to model the DNA damage response network controlled by the Yeast-specific AP-1 (YAP) family of transcription factors. This analysis reveals that YAP regulatory specificity is achieved by at least three mechanisms: ( i ) ergence of DNA-binding sequences into two subfamilies ( ii ) condition-specific combinatorial regulation by multiple Yap factors and ( iii ) interactions of Yap 1, 4, and 6 with chromatin remodeling proteins. Additional microarray experiments establish that Yap 4 and 6 regulate gene expression through interactions with the histone deacetylase, Hda1. The data further highlight differences among Yap paralogs in terms of their regulatory mode of action (activation vs. repression). This study suggests how other large TF families might be disentangled in the future.
Publisher: Society for Neuroscience
Date: 07-10-2009
DOI: 10.1523/JNEUROSCI.3180-09.2009
Abstract: Human immunodeficiency virus (HIV)-associated dementia (HAD) is a syndrome occurring in HIV-infected patients with advanced disease that likely develops as a result of macrophage and microglial activation as well as other immune events triggered by virus in the central nervous system. The most relevant experimental model of HAD, rhesus macaques exhibiting simian immunodeficiency virus (SIV) encephalitis (SIVE), closely reproduces the human disease and has been successfully used to advance our understanding of mechanisms underlying HAD. In this study we integrate gene expression data from uninfected and SIV-infected hippoc us with a human protein interaction network and discover modules of genes whose expression patterns distinguish these two states, to facilitate identification of neuronal genes that may contribute to SIVE/HIV cognitive deficits. Using this approach we identify several downregulated candidate genes and select one, EGR1, a key molecule in hippoc us-related learning and memory, for further study. We show that EGR1 is downregulated in SIV-infected hippoc us and that it can be downregulated in differentiated human neuroblastoma cells by treatment with CCL8, a product of activated microglia. Integration of expression data with protein interaction data to discover discriminatory modules of interacting proteins can be usefully used to prioritize differentially expressed genes for further study. Investigation of EGR1, selected in this manner, indicates that its downregulation in SIVE may occur as a consequence of the host response to infection, leading to deficits in cognition.
Publisher: Elsevier BV
Date: 04-2010
Publisher: Oxford University Press (OUP)
Date: 13-07-2010
DOI: 10.1093/BIOINFORMATICS/BTQ407
Abstract: Motivation: The recently proposed Systems Biology Graphical Notation (SBGN) provides a standard for the visual representation of biochemical and cellular processes. It aims to support more efficient and accurate communication of biological knowledge between different research communities in the life sciences. However, to increase the use of SBGN, tools for editing, validating and translating SBGN maps are desirable. Results: We present SBGN-ED, a tool which allows the creation of all three types of SBGN maps from scratch or the editing of existing maps, the validation of these maps for syntactical and semantical correctness, the translation of networks from the KEGG and MetaCrop databases into SBGN and the export of SBGN maps into several file and image formats. Availability: SBGN-ED is freely available from vanted.ipk-gatersleben.de/addons/sbgn-ed. The web site contains also tutorials and ex le files. Contact: schreibe@ipk-gatersleben.de
Publisher: Springer Science and Business Media LLC
Date: 09-05-2022
Publisher: Cold Spring Harbor Laboratory
Date: 26-10-2010
Abstract: Transcriptional networks have been shown to evolve very rapidly, prompting questions as to how such changes arise and are tolerated. Recent comparisons of transcriptional networks across species have implicated variations in the cis -acting DNA sequences near genes as the main cause of ergence. What is less clear is how these changes interact with trans -acting changes occurring elsewhere in the genetic circuit. Here, we report the discovery of a system of compensatory trans and cis mutations in the yeast AP-1 transcriptional network that allows for conserved transcriptional regulation despite continued genetic change. We pinpoint a single species, the fungal pathogen Candida glabrata , in which a trans mutation has occurred very recently in a single AP-1 family member, distinguishing it from its Saccharomyces ortholog. Comparison of chromatin immunoprecipitation profiles between Candida and Saccharomyces shows that, despite their different DNA-binding domains, the AP-1 orthologs regulate a conserved block of genes. This conservation is enabled by concomitant changes in the cis -regulatory motifs upstream of each gene. Thus, both trans and cis mutations have perturbed the yeast AP-1 regulatory system in such a way as to compensate for one another. This demonstrates an ex le of “coevolution” between a DNA-binding transcription factor and its cis -regulatory site, reminiscent of the coevolution of protein binding partners.
Publisher: Oxford University Press (OUP)
Date: 04-02-0001
DOI: 10.1093/BIOINFORMATICS/BTQ376
Abstract: Motivation: Nonlinear small datasets, which are characterized by low numbers of s les and very high numbers of measures, occur frequently in computational biology, and pose problems in their investigation. Unsupervised hybrid-two-phase (H2P) procedures—specifically dimension reduction (DR), coupled with clustering—provide valuable assistance, not only for unsupervised data classification, but also for visualization of the patterns hidden in high-dimensional feature space. Methods: ‘Minimum Curvilinearity’ (MC) is a principle that—for small datasets—suggests the approximation of curvilinear s le distances in the feature space by pair-wise distances over their minimum spanning tree (MST), and thus avoids the introduction of any tuning parameter. MC is used to design two novel forms of nonlinear machine learning (NML): Minimum Curvilinear embedding (MCE) for DR, and Minimum Curvilinear affinity propagation (MCAP) for clustering. Results: Compared with several other unsupervised and supervised algorithms, MCE and MCAP, whether in idually or combined in H2P, overcome the limits of classical approaches. High performance was attained in the visualization and classification of: (i) pain patients (proteomic measurements) in peripheral neuropathy (ii) human organ tissues (genomic transcription factor measurements) on the basis of their embryological origin. Conclusion: MC provides a valuable framework to estimate nonlinear distances in small datasets. Its extension to large datasets is prefigured for novel NMLs. Classification of neuropathic pain by proteomic profiles offers new insights for future molecular and systems biology characterization of pain. Improvements in tissue embryological classification refine results obtained in an earlier study, and suggest a possible reinterpretation of skin attribution as mesodermal. Availability: ite/carlovittoriocannistraci/home Contact: kalokagathos.agon@gmail.com massimo.alessio@hsr.it Supplementary information: Supplementary data are available at Bioinformatics online.
Location: United States of America
No related grants have been discovered for Trey Ideker.