Role-similarity based functional prediction in networked systems: Application to the yeast proteome

We propose a general method to predict functions of vertices where: 1. The wiring of the network is somehow related to the vertex functionality. 2. A fraction of the vertices are functionally classified. The method is influenced by role-similarity measures of social network analysis. The two versions of our prediction scheme is tested on model networks were the functions of the vertices are designed to match their network surroundings. We also apply these methods to the proteome of the yeast Saccharomyces cerevisiae and find the results compatible with more specialized methods

A Series of N-terminal Epitope Tagged Hdh Knock-In Alleles Expressing Normal and Mutant Huntingtin: Their Application to Understanding the Effect of Increasing the Length of Normal Huntingtin’s Polyglutamine Stretch on CAG140 Mouse Model Pathogenesis

Background: Huntington’s disease (HD) is an autosomal dominant neurodegenerative disease that is caused by the expansion of a polyglutamine (polyQ) stretch within Huntingtin (htt), the protein product of the HD gene. Although studies in vitro have suggested that the mutant htt can act in a potentially dominant negative fashion by sequestering wild-type htt into insoluble protein aggregates, the role of the length of the normal htt polyQ stretch, and the adjacent proline-rich region (PRR) in modulating HD mouse model pathogenesis is currently unknown. Results: We describe the generation and characterization of a series of knock-in HD mouse models that express versions of the mouse HD gene (Hdh) encoding N-terminal hemaglutinin (HA) or 3xFlag epitope tagged full-length htt with different polyQ lengths (HA7Q-, 3xFlag7Q-, 3xFlag20Q-, and 3xFlag140Q-htt) and substitution of the adjacent mouse PRR with the human PRR (3xFlag20Q- and 3xFlag140Q-htt). Using co-immunoprecipitation and immunohistochemistry analyses, we detect no significant interaction between soluble full-length normal 7Q- htt and mutant (140Q) htt, but we do observe N-terminal fragments of epitope-tagged normal htt in mutant htt aggregates. When the sequences encoding normal mouse htt’s polyQ stretch and PRR are replaced with non-pathogenic human sequence in mice also expressing 140Q-htt, aggregation foci within the striatum, and the mean size of htt inclusions are increased, along with an increase in striatal lipofuscin and gliosis. Conclusion: In mice, soluble full-length normal and mutant htt are predominantly monomeric. In heterozygous knock-in HD mouse models, substituting the normal mouse polyQ and PRR with normal human sequence can exacerbate some neuropathological phenotypes

Effective and Efficient Similarity Index for Link Prediction of Complex Networks

Predictions of missing links of incomplete networks like protein-protein interaction networks or very likely but not yet existent links in evolutionary networks like friendship networks in web society can be considered as a guideline for further experiments or valuable information for web users. In this paper, we introduce a local path index to estimate the likelihood of the existence of a link between two nodes. We propose a network model with controllable density and noise strength in generating links, as well as collect data of six real networks. Extensive numerical simulations on both modeled networks and real networks demonstrated the high effectiveness and efficiency of the local path index compared with two well-known and widely used indices, the common neighbors and the Katz index. Indeed, the local path index provides competitively accurate predictions as the Katz index while requires much less CPU time and memory space, which is therefore a strong candidate for potential practical applications in data mining of huge-size networks.Comment: 8 pages, 5 figures, 3 table

Link Prediction Based on Local Random Walk

The problem of missing link prediction in complex networks has attracted much attention recently. Two difficulties in link prediction are the sparsity and huge size of the target networks. Therefore, the design of an efficient and effective method is of both theoretical interests and practical significance. In this Letter, we proposed a method based on local random walk, which can give competitively good prediction or even better prediction than other random-walk-based methods while has a lower computational complexity.Comment: 6 pages, 2 figure

B655: Maine Egg Marketing: A Structural Study

This study, from 1967, was designed to provide basic information concerning the movement of table eggs through the major marketing firms located in Maine. The primary purpose of the report was to aid in better understanding the structure of the present egg marketing systems in Maine in order that: (1) efficient alternatives to the present egg marketing systems could be developed, and (2) Maine\u27s competitive position in out-of-state markets could be improved.https://digitalcommons.library.umaine.edu/aes_bulletin/1036/thumbnail.jp

The Presidential Succession Act at 75 | Keynote Address

These remarks were delivered as part of the program entitled The Presidential Succession Act at 75: Praise It or Bury It?, which was held on April 6, 2022, and hosted by the Fordham University School of Law. The Presidential Succession Act sets out the presidential line of succession and other procedures for situations in which the president and vice president have both died, resigned, been removed, or become unable to discharge the presidency’s powers and duties. The Act also addresses succession scenarios before Inauguration Day. In light of the statute’s seventy-fifth anniversary, this program explored relevant history and analyzed whether reform to the statute is needed. In these remarks, former Homeland Security Secretary Jeh C. Johnson, a Partner at Paul, Weiss, Rifkind, Wharton & Garrison LLP, draws on his experience as an official in the presidential line of succession. Secretary Johnson served as the “designated survivor” for the 2016 State of the Union Address and the 2017 Inauguration

National Security Law, Lawyers, and Lawyering in the Obama Administration

Thank you for this invitation, and thank you, in particular, Professor Hathaway, for your work in the national security legal field. Since we first met last fall, I have appreciated your scholarship and our growing friendship. I was pleased to welcome you to the Pentagon in December to introduce you to a number of my civilian and military colleagues there. I would like to count on you as someone with whom I can consult from time to time on the very difficult legal issues we wrestle with in national security