Conditional random field approach to prediction of protein-protein interactions using domain information

For understanding cellular systems and biological networks, it is important to analyze functions and interactions of proteins and domains. Many methods for predicting protein-protein interactions have been developed. It is known that mutual information between residues at interacting sites can be higher than that at non-interacting sites. It is based on the thought that amino acid residues at interacting sites have coevolved with those at the corresponding residues in the partner proteins. Several studies have shown that such mutual information is useful for identifying contact residues in interacting proteins

Algorithms and Complexity Analyses for Control of Singleton Attractors in Boolean Networks

A Boolean network (BN) is a mathematical model of genetic networks. We propose several algorithms for control of singleton attractors in BN. We theoretically estimate the average-case time complexities of the proposed algorithms, and confirm them by computer experiments. The results suggest the importance of gene ordering. Especially, setting internal nodes ahead yields shorter computational time than setting external nodes ahead in various types of algorithms. We also present a heuristic algorithm which does not look for the optimal solution but for the solution whose computational time is shorter than that of the exact algorithms

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in O(1.19 n)timeforK = 2, which is much faster than the naive O(2 n) time algorithm, where n is the number of genes and K is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard

Steering the Climate System: Using Inertia to Lower the Cost of Policy

Conventional wisdom holds that the efficient way to limit warming to a chosen level is to price carbon emissions at a rate that increases exponentially. We show that this “Hotelling” tax on carbon emissions is actually inefficient. The least-cost policy path takes advantage of the climate system’s inertia by growing more slowly than exponentially. Carbon dioxide temporarily overshoots the steady-state level consistent with the temperature limit, and the efficient carbon tax follows an inverse-U-shaped path. Economic models that assume exponentially increasing carbon taxes are overestimating the minimum cost of limiting warming, overestimating the efficient near-term carbon tax, and overvaluing technologies that mature sooner

Carcinosarcoma of the Sigmoid Colon: Report of a Case

Our case was a 65-year-old male, with the chief complaints of diarrhea and abdominal distention. Three years earlier, the patient had undergone transcatheter arterial embolization and radiofrequency treatment based on a diagnosis of hepatocellular carcinoma due to hepatitis B by another doctor. In October 2007, the patient developed diarrhea and increased abdominal distention. In December, CT examination conducted by the previous doctor revealed a 20-cm tumor within the pelvis. The patient was diagnosed with sigmoid colon cancer based on barium enema examination using gastrografin, and was introduced to our hospital for treatment. He was diagnosed with low-differentiated carcinoma by biopsy of the colon during endoscopy and underwent sigmoidectomy based on a diagnosis of sigmoid colon cancer. The tumor had infiltrated the bladder, and a tumorectomy was conducted through partially combined resection. The tumor was a huge lesion occupying the inside of the lumen, and histopathological findings revealed that the tumor, the main part of which lay beneath the mucous membrane, had a transitional image composed of both spindle-shaped atypical cells and sarcomatoid shape. The result of immunostaining was CK7(+), CK20(-), AFP(-), and the patient was diagnosed as having carcinosarcoma of the colon. Carcinosarcoma of the colon is a malignant tumor with poor prognosis, and the mean survival period in past reports was approximately 6 months. The patient was treated with FOLFIRI+Bevacizumab therapy according to chemotherapy for colon cancer, but he was refractory to the therapy

Association between the rs1465040 single-nucleotide polymorphism close to the transient receptor potential subfamily C member 3 (TRPC3) gene and postoperative analgesic requirements

AbstractAn association between postoperative analgesic requirements in subjects who underwent orthognathic surgery and the rs1465040 single-nucleotide polymorphism close to the transient receptor potential subfamily C member 3 (TRPC3) gene was suggested by our previous genome-wide association study. To verify this association, we analyzed the association between the rs1465040 SNP and analgesic requirements, including opioid requirements, after open abdominal surgery. The association between the rs1465040 SNP and postoperative analgesic requirements was confirmed in the open abdominal surgery group (P = 0.036), suggesting that the TRPC3 SNP may contribute to predicting postoperative analgesic requirements

Comparing biological networks via graph compression

<p>Abstract</p> <p>Background</p> <p>Comparison of various kinds of biological data is one of the main problems in bioinformatics and systems biology. Data compression methods have been applied to comparison of large sequence data and protein structure data. Since it is still difficult to compare global structures of large biological networks, it is reasonable to try to apply data compression methods to comparison of biological networks. In existing compression methods, the uniqueness of compression results is not guaranteed because there is some ambiguity in selection of overlapping edges.</p> <p>Results</p> <p>This paper proposes novel efficient methods, CompressEdge and CompressVertices, for comparing large biological networks. In the proposed methods, an original network structure is compressed by iteratively contracting identical edges and sets of connected edges. Then, the similarity of two networks is measured by a compression ratio of the concatenated networks. The proposed methods are applied to comparison of metabolic networks of several organisms, <it>H. sapiens, M. musculus, A. thaliana, D. melanogaster, C. elegans, E. coli, S. cerevisiae,</it> and <it>B. subtilis,</it> and are compared with an existing method. These results suggest that our methods can efficiently measure the similarities between metabolic networks.</p> <p>Conclusions</p> <p>Our proposed algorithms, which compress node-labeled networks, are useful for measuring the similarity of large biological networks.</p