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Data mining algorithms and sequencing methods (such as RNA-seq and ChIP-seq) are being combined to discover genomic regulatory motifs that relate to a variety of phenotypes. However, motif discovery algorithms often produce very long lists of putative transcription factor binding sites, hindering the discovery of phenotype-related regulatory elements by making it difficult to select a manageable set of candidate motifs for experimental validation. To address this issue, the authors introduce the motif selection problem and provide coverage-based search heuristics for its solution. Analysis of 203 ChIP-seq experiments from the ENCyclopedia of DNA Elements project shows that our algorithms produce motifs that have high sensitivity and specificity and reveals new insights about the regulatory code of the human genome. The greedy algorithm performs the best, selecting a median of two motifs per ChIP-seq transcription factor group while achieving a median sensitivity of 77 percent.

Motivation De novo motif discovery algorithms find statistically over-represented sequence motifs that may function as transcription factor binding sites. Current methods often report large numbers of motifs, making it difficult to perform further analyses and experimental validation. The motif selection problem seeks to identify a minimal set of putative regulatory motifs that characterize sequences of interest (e.g. ChIP-Seq binding regions). Results In this study, the motif selection problem is mapped to variants of the set cover problem that are solved via tabu search and by relaxed integer linear programing (RILP). The algorithms are employed to analyze 349 ChIP-Seq experiments from the ENCODE project, yielding a small number of high-quality motifs that represent putative binding sites of primary factors and cofactors. Specifically, when compared with the motifs reported by Kheradpour and Kellis, the set cover-based algorithms produced motif sets covering 35% more peaks for 11 TFs and identified 4 more putative cofactors for 6 TFs. Moreover, a systematic evaluation using nested cross-validation revealed that the RILP algorithm selected fewer motifs and was able to cover 6% more peaks and 3% fewer background regions, which reduced the error rate by 7%. Availability and implementation The source code of the algorithms and all the datasets are available at https://github.com/YichaoOU/Set_cover_tools. Supplementary information Supplementary data are available at Bioinformatics online.

The solutions of certain natural decision problems such as the halting problem and the boolean satisfiability problem contain large amounts of useful information about computation that is highly organized and readily available to efficient computational processes. Such problems are computationally useful. This dissertation investigates the complexity and distribution of these computationally useful problems. The main results of this dissertation are of the following three general types. (1) Useful problems contain highly organized information. (2) Very useful problems are so highly organized that they are unusually simple and hence rare. (3) Useful problems are, as a whole, not rare and thus are not necessarily simple. A result of type (1) is proven in Chapter 3. Bennett recently extended algorithmic information theory to include a notion of computational depth that appears to quantify the level of organization in binary strings and sequences. The main result of Chapter 3 states that every weakly useful sequence is strongly deep. (A sequence x is weakly useful if a non-negligible set of recursive problems are decidable within a fixed recursive time bound when given access to x.) Results of type (2) are presented in Chapters 4 and 5. These results say that the $\le\sbsp{\rm m}{\rm P}$-complete problems for E = DTIME(2$\sp{\rm linear}$) and the $\le\sbsp{\rm m}{\rm p/poly}$-complete problems for ESPACE = DSPACE(2$\sp{\rm linear}$) are unusually simple and hence rare. Complete problems are very useful because every problem in E or ESPACE is efficiently decidable when given access to one of these problems. Chapter 6 develops a result of type (3). This result says that the weakly $\le\sbsp{\rm m}{\rm P}$-complete problems for E and ESPACE are not rare and hence are not necessarily simple. Weakly complete problems are useful because every problem in a non-negligible subset of E or ESPACE is efficiently decidable when given access to one of these problems. The above results (and others along the way) are obtained through a systematic investigation of the measure-theoretic structure of complexity classes.

High DGAT1 expression levels in the small intestine highlight the critical role this enzyme plays in nutrient absorption. Identification of inhibitors which predominantly inhibit DGAT1 in the gut is an attractive drug discovery strategy with anticipated benefits of reduced systemic toxicity. In this report we describe our discovery and optimization of DGAT1 inhibitors whose plasma exposure is minimized by the action of transporters, including the P-glycoprotein transporter. The impact of this unique absorption profile on efficacy in rat and dog efficacy models is presented.

This paper presents a new polynomial-time algorithm, approximate star bicoloring (ASBC), for star bicoloring and acyclic bicoloring. These NP-complete combinatorial problems arise from problems associated with computing large sparse Jacobian matrices. The main results of this paper lie in approximation analysis related to these problems. In particular, it is shown that (i) both star and acyclic bicoloring can be approximated in polynomial time to the ratio O(n 2/3) and (ii) both star and acyclic bicoloring cannot be approximated to the ratio O(n 1/3−e) in polynomial time under reasonable complexity theoretic hypotheses. The ASBC algorithm is also analysed experimentally on a collection of realistic test cases from the Harwell–Boeing sparse matrix collection. The experimental results indicate that ASBC performs quite well in practice; the performance of the new algorithm always fell within the range of 1.53 and 6 times optimal on the given test sets.

Exosomes are small membrane vesicles of endocytic origin that are secreted by most cells in culture, but are also present in serum. They contain a wide array of protein ligands on their surface, which has led to the hypothesis that they might mediate intercellular communication. Indeed, data support that exosomes can transfer Ags to dendritic cells (DC), and, interestingly, that these DC can subsequently induce T cell priming or tolerance. We have investigated whether this concept can be expanded to antiviral immunity. We isolated exosomes from supernatant of cultured bone marrow-derived DC (BMDC) that were infected with lymphocytic choriomeningitis virus (LCMV) or loaded with an immunodominant LCMV peptide, and characterized them by flow cytometry upon binding to beads. We then incubated the exosome preparations with BMDC and looked at their potential to activate LCMV gp33-specific naive and memory CD8 T cells. We found that exosomes do not significantly contribute to CD8 T cell cross-priming in vitro. Additionally, exosomes derived from in vitro-infected BMDC did not exhibit significant in vivo priming activity, as evidenced by the lack of protection following exosome vaccination. Thus, DC-derived exosomes do not appear to contribute significantly to CTL priming during acute LCMV infection.

Aim: To evaluate the association between inhibition of dipeptidyl peptidase (DPP)-8 and/or DPP-9 organ toxicities and mortality in rodents. Research Design and Methods: The relative selectivity of the DPP-4 inhibitor, vildagliptin, was determined by comparing its KI (concentration of compound yielding 50% inhibition of the enzyme) values for inhibition of recombinant human DPP-4, DPP-8 and DPP-9 assessed in vitro. In experiments performed in vivo, vildagliptin was administered by gavage for 13 weeks, at doses up to 1500 mg/kg/day in CD-1 mice and at doses up to 900 mg/kg/day in Wistar rats. Plasma concentrations of vildagliptin were assessed at week 12, and toxicities previously ascribed to inhibition of DPP-8 and/or DPP-9 were assessed at week 13. Results: The KI values for vildagliptin-induced inhibition of DPP-4, DPP-8 and DPP-9 were 3, 810 and 95 nM respectively. The mean plasma concentration 24 h after dose after 12-week daily dosing with 1500 mg/kg/day in mice was 2279 nM. The mean plasma drug level 24 h after dose after 12-week daily dosing with 900 mg/kg/day in rats was 5729 nM. These high doses maintained plasma drug levels well above the KI values for DPP-8 and DPP-9 throughout a 24-h period. At these high doses, the toxicities of a selective DPP-8/DPP-9 inhibitor that were reported previously (100% mortality in mice, alopecia, thrombocytopenia, reticulocytopenia, enlarged lymph nodes, splenomegaly and 20% mortality in rats) were not observed. Conclusions: Inhibition of DPP-8 and DPP-9 per se does not lead to organ toxicities and mortality in rodents. Thus, a mechanism other than DPP-8/DPP-9 inhibition likely underlies the toxicity previously reported to be associated with a selective DPP-8/DPP-9 inhibitor.

In 1996 Khanna and Motwani proposed three logic-based optimization problems constrained by planar structure, and offered the hypothesis that these putatively fundamental problems might provide insight into characterizing the class of optimization problems that admit a polynomial-time approximation scheme (PTAS). The main contribution of this paper is to explore this program from the point of view of parameterized complexity. Problems of optimization are naturally parameterized by the parameter k = 1/?. An optimization problem admits a PTAS if and only if there is an algorithm ?, that, given an input of size n, and a parameter value k = 1/?, produces a solution that is within a multiplicative factor of (1+ ?) of optimal, in a running time that is polynomial for every fixed value of ?. This definition admits the possibility that the degree of the polynomial that bounds the running time of ? may increase, even quite dramatically, as a function of k = 1/?. In fact, amongst the PTASs that are currently known, for an error of 20%, polynomial-time bounds no better than O(n2000) are quite common. Viewing k = 1/? as a problem parameter, in the sense of parameterized complexity, leads naturally to the question of whether an efficient PTAS (EPTAS) might be possible for a given optimization problem. An EPTAS is simply a fixed-parameter tractable algorithm with respect to this parameter. We offer a number of results concerning the problems Planar TMIN, Planar TMAX and Planar MPSAT defined by Khanna and Motwani: (1) We show that each of these problems of approximation, naturally parameterized by k = 1/?, is hard for W[1], and thus it is highly unlikely that they admit EPTASs. (One could also interpret this as indicating that PTASs for these problems are unlikely to be a useful way of coping with intractability in the sense of Garey and Johnson.) (2) We show that there are EPTASs for some subproblems described by syntactic restrictions, and establish some limits on how far these positive results can be extended.

This paper addresses the problem of resource allocation for distributed real-time periodic tasks, operating in environments that undergo unpredictable changes and that defy the specification of meaningful worst-case execution times. These tasks are supplied by input data originating from various environmental workload sources. Rather than using worst-case execution times (WCETs) to describe the CPU usage of the tasks, we assume here that execution profiles are given to describe the running time of the tasks in terms of the size of the input data of each workload source. The objective of resource allocation is to produce an initial allocation that is robust against fluctuations in the environmental parameters. We try to maximize the input size (workload) that can be handled by the system, and hence to delay possible (costly) reallocations as long as possible. We present an approximation algorithm based on first-fit and binary search that we call FFBS. As we show here, the first-fit algorithm produces solutions that are often close to optimal. In particular, we show analytically that FFBS is guaranteed to produce a solution that is at least 41% of optimal, asymptotically, under certain reasonable restrictions on the running times of tasks in the system. Moreover, we show that if at most 12% of the system utilization is consumed by input independent tasks (e.g., constant time tasks), then FFBS is guaranteed to produce a solution that is at least 33% of optimal, asymptotically. Moreover, we present simulations to compare FFBS approximation algorithm with a set of standard (local search) heuristics such as hill-climbing, simulated annealing, and random search. The results suggest that FFBS, in combination with other local improvement strategies, may be a reasonable approach for resource allocation in dynamic real-time systems.

Mot1 is an essential Snf2/Swi2-related ATPase and TATA-binding protein (TBP)-associated factor (TAF). In vitro, Mot1 utilizes ATP hydrolysis to disrupt TBP–DNA complexes, but the relationship of this activity to Mot1's in vivo function is unclear. Chromatin immunoprecipitation was used to determine how Mot1 affects the assembly of preinitiation complexes (PICs) at Mot1-controlled promoters in vivo. We find that the Mot1-repressed HSP26 and INO1 promoters are both regulated by TBP recruitment; inactivation of Mot1 leads to increased PIC formation coincident with derepression of transcription. For the Mot1-activated genes BNA1 and URA1, inactivation of Mot1 also leads, remarkably, to increased TBP binding to the promoters, despite the fact that transcription of these genes is obliterated in mot1 cells. In contrast, levels of Taf1, TFIIB, and RNA polymerase II are reduced at Mot1-activated promoters in mot1 cells. These results suggest that Mot1-mediated displacement of TBP underlies its mechanism of repression and activation at these genes. We suggest that at activated promoters, Mot1 disassembles transcriptionally inactive TBP, thereby facilitating the formation of a TBP complex that supports functional PIC assembly.