Person:
Yu, Haiyuan

Profile Picture

Email Address

AA Acceptance Date

Birth Date

Research Projects

Organizational Units

Job Title

Last Name

Yu

First Name

Haiyuan

Name

Yu, Haiyuan
Author's Publications: search.filters.isAuthorOfPublication.0a63b4fa-3bdd-47ef-9905-e5e5f74e489d

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    Publication
    Edgetic Perturbation Models of Human Inherited Disorders
    (Nature Publishing Group, 2009) Simonis, Nicolas; Li, Qian-Ru; Heuze, Fabien; Klitgord, Niels; Tam, Stanley; Venkatesan, Kavitha; Mou, Danny; Swearingen, Venus; Yildirim, Muhammed; Dricot, Amélie; Szeto, David; Lin, Chenwei; Hao, Tong; Fan, Changyu; Milstein, Stuart; Dupuy, Denis; Brasseur, Robert; Zhong, Quan; Charloteaux, Benoit; Yu, Haiyuan; Yan, Han; Hill, David; Cusick, Michael; Vidal, Marc
    Cellular functions are mediated through complex systems of macromolecules and metabolites linked through biochemical and physical interactions, represented in interactome models as ‘nodes' and ‘edges', respectively. Better understanding of genotype-to-phenotype relationships in human disease will require modeling of how disease-causing mutations affect systems or interactome properties. Here we investigate how perturbations of interactome networks may differ between complete loss of gene products (‘node removal') and interaction-specific or edge-specific (‘edgetic') alterations. Global computational analyses of ~50 000 known causative mutations in human Mendelian disorders revealed clear separations of mutations probably corresponding to those of node removal versus edgetic perturbations. Experimental characterization of mutant alleles in various disorders identified diverse edgetic interaction profiles of mutant proteins, which correlated with distinct structural properties of disease proteins and disease mechanisms. Edgetic perturbations seem to confer distinct functional consequences from node removal because a large fraction of cases in which a single gene is linked to multiple disorders can be modeled by distinguishing edgetic network perturbations. Edgetic network perturbation models might improve both the understanding of dissemination of disease alleles in human populations and the development of molecular therapeutic strategies.
  • Thumbnail Image
    Publication
    The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics
    (Public Library of Science, 2007) Yu, Haiyuan; Kim, Philip M.; Sprecher, Emmett; Trifonov, Valery; Gerstein, Mark
    It has been a long-standing goal in systems biology to find relations between the topological properties and functional features of protein networks. However, most of the focus in network studies has been on highly connected proteins (“hubs”). As a complementary notion, it is possible to define bottlenecks as proteins with a high betweenness centrality (i.e., network nodes that have many “shortest paths” going through them, analogous to major bridges and tunnels on a highway map). Bottlenecks are, in fact, key connector proteins with surprising functional and dynamic properties. In particular, they are more likely to be essential proteins. In fact, in regulatory and other directed networks, betweenness (i.e., “bottleneck-ness”) is a much more significant indicator of essentiality than degree (i.e., “hub-ness”). Furthermore, bottlenecks correspond to the dynamic components of the interaction network—they are significantly less well coexpressed with their neighbors than nonbottlenecks, implying that expression dynamics is wired into the network topology.
  • Thumbnail Image
    Publication
    Bayesian Modeling of the Yeast SH3 Domain Interactome Predicts Spatiotemporal Dynamics of Endocytosis Proteins
    (Public Library of Science, 2009) Tonikian, Raffi; Xin, Xiaofeng; Toret, Christopher P.; Gfeller, David; Landgraf, Christiane; Panni, Simona; Paoluzi, Serena; Castagnoli, Luisa; Currell, Bridget; Seshagiri, Somasekar; Winsor, Barbara; Gerstein, Mark B.; Bader, Gary D.; Volkmer, Rudolf; Cesareni, Gianni; Drubin, David G.; Kim, Philip M.; Sidhu, Sachdev S.; Boone, Charles; Yu, Haiyuan; Vidal, Marc
    SH3 domains are peptide recognition modules that mediate the assembly of diverse biological complexes. We scanned billions of phage-displayed peptides to map the binding specificities of the SH3 domain family in the budding yeast, Saccharomyces cerevisiae. Although most of the SH3 domains fall into the canonical classes I and II, each domain utilizes distinct features of its cognate ligands to achieve binding selectivity. Furthermore, we uncovered several SH3 domains with specificity profiles that clearly deviate from the two canonical classes. In conjunction with phage display, we used yeast twohybrid and peptide array screening to independently identify SH3 domain binding partners. The results from the three complementary techniques were integrated using a Bayesian algorithm to generate a high-confidence yeast SH3 domain interaction map. The interaction map was enriched for proteins involved in endocytosis, revealing a set of SH3-mediated interactions that underlie formation of protein complexes essential to this biological pathway. We used the SH3 domain interaction network to predict the dynamic localization of several previously uncharacterized endocytic proteins, and our analysis suggests a novel role for the SH3 domains of Lsb3p and Lsb4p as hubs that recruit and assemble several endocytic complexes.