Refining interaction search through signed iterative Random Forests

Advances in supervised learning have enabled accurate prediction in biological systems governed by complex interactions among biomolecules. However, state-of-the-art predictive algorithms are typically black-boxes, learning statistical interactions that are difficult to translate into testable hypotheses. The iterative Random Forest algorithm took a step towards bridging this gap by providing a computationally tractable procedure to identify the stable, high-order feature interactions that drive the predictive accuracy of Random Forests (RF). Here we refine the interactions identified by iRF to explicitly map responses as a function of interacting features. Our method, signed iRF, describes subsets of rules that frequently occur on RF decision paths. We refer to these rule subsets as signed interactions. Signed interactions share not only the same set of interacting features but also exhibit similar thresholding behavior, and thus describe a consistent functional relationship between interacting features and responses. We describe stable and predictive importance metrics to rank signed interactions. For each SPIM, we define null importance metrics that characterize its expected behavior under known structure. We evaluate our proposed approach in biologically inspired simulations and two case studies: predicting enhancer activity and spatial gene expression patterns. In the case of enhancer activity, s-iRF recovers one of the few experimentally validated high-order interactions and suggests novel enhancer elements where this interaction may be active. In the case of spatial gene expression patterns, s-iRF recovers all 11 reported links in the gap gene network. By refining the process of interaction recovery, our approach has the potential to guide mechanistic inquiry into systems whose scale and complexity is beyond human comprehension

Sequence analysis of the cis-regulatory regions of the bithorax complex of Drosophila

The bithorax complex (BX-C) of Drosophila, one of two complexes that act as master regulators of the body plan of the fly, has now been entirely sequenced and comprises approximate to 315,000 bp, only 1.4% of which codes for protein. Analysis of this sequence reveals significantly overrepresented DNA motifs of unknown, as well as known, functions in the nonprotein-coding portion of the sequence. The following types of motifs in that portion are analyzed: (i) concatamers of mono-, di-, and trinucleotides; (ii) tightly clustered hexanucleotides (spaced less than or equal to 5 bases apart); (iii) direct and reverse repeats longer than 20 bp; and (iv) a number of motifs known from biochemical studies to play a role in the regulation of the BX-C. The hexanucleotide AGATAC is remarkably overrepresented and is surmised to play a role in chromosome pairing. The positions of sites of highly overrepresented motifs are plotted for those that occur at more than five sites in the sequence, when <0.5 case is expected. Expected values are based on a third-order Markov chain, which is the optimal order for representing the BXCALL sequence

Drosophila by the dozen

A report of the 48th Annual Drosophila Research Conference, Philadelphia, USA, 7-11 March 2007

Complete Genome Sequence of the Citrobacter freundii Type Strain.

Citrobacter freundii is a species of facultative anaerobic Gram-negative bacteria of the family Enterobacteriaceae The complete genome is composed of a single chromosomal circle of 4,957,773 bp with a G+C content of 52%

Characterization of MtnE, the fifth metallothionein member in Drosophila

Metallothioneins (MTs) constitute a family of cysteine-rich, low molecular weight metal-binding proteins which occur in almost all forms of life. They bind physiological metals, such as zinc and copper, as well as nonessential, toxic heavy metals, such as cadmium, mercury, and silver. MT expression is regulated at the transcriptional level by metal-regulatory transcription factor1 (MTF-1), which binds to the metal-response elements (MREs) in the enhancer/promoter regions of MT genes. Drosophila was thought to have four MT genes, namely, MtnA, MtnB, MtnC, and MtnD. Here we characterize a new fifth member of Drosophila MT gene family, coding for metallothionein E (MtnE). The MtnE transcription unit is located head-to-head with the one of MtnD. The intervening sequence contains four MREs which bind, with different affinities, to MTF-1. Both of the divergently transcribed MT genes are completely dependent on MTF-1, whereby MtnE is consistently more strongly transcribed. MtnE expression is induced in response to heavy metals, notably copper, mercury, and silver, and is upregulated in a genetic background where the other four MTs are missin

ShapeWright--finite element based free-form shape design

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1990.Includes bibliographical references (p. 179-192).by George Celniker.Ph.D

Correction: Benchmarking tools for the alignment of functional noncoding DNA

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.AbstractIn follow-up studies to this work [1], we have identified an error in a single line of code responsible for parsing BLASTZ [2] alignments that affects our previously published results for this alignment tool. This error resulted in a reduction in overall alignment coverage, with a concomitant underestimation of alignment sensitivity and overestimation of alignment specificity. As BLASTZ is an important and widely used alignment tool, we present here the revised results of our performance evaluations for BLASTZ together with previously reported results for the other alignment tools studied, which have been subsequently verified (Figures 1-4). The general conclusions presented in [1] remain unchanged, although the following sections concerning BLASTZ performance must be modified in light of our recent findings. The true overall alignment coverage for BLASTZ with and without insertion/deletion evolution and with and without blocks of constraint is shown in Figure 1, and reveals increased overall coverage in the presence of constrained blocks for intermediate to high divergence distances (Figures 1C & 1D) relative to previous results ([1] Figures 3C & 3D). As a consequence, the true overall sensitivity for BLASTZ is increased for intermediate to high divergence distances, especially in the presence of insertion/deletion evolution and constrained blocks (Figure 2D) relative to previous results ([1] Figure 4D). The most important revisions to [1] concern BLASTZ performance in interspersed blocks of constrained sequences (Figures 3, 4). Figure 3 shows that the true constraint coverage, and therefore constraint sensitivity, of BLASTZ is much improved relative to previous results for intermediate to high divergence distances ([1], Figure 5). Thus BLASTZ has increased constraint coverage relative to overall coverage (cp. Figures 1C & 1D with 3A & 3B), indicating that BLASTZ local alignments preferentially occur in constrained sequences for intermediate to high divergence distances, overturning claims on page 6 of [1] to the contrary. Likewise, the claim that BLASTZ has a "dramatic decrease in constraint sensitivity in the presence of indel evolution" on page 10 of [1] is incorrect. The increase in overall coverage, however, decreases the constraint specificity of BLASTZ for intermediate to high divergence distances (Figure 4A & 4B) relative to previous results ([1] Figure 6A & 6B). This decrease in constraint specificity requires reconsideration of the use of BLASTZ local alignments as specific detectors of constrained noncoding sequences discussed page 10 of [1]. Revised performance statistics for BLASTZ are posted along with previous results at [3]. We apologize for any misconception or inconvenience this error may have caused. References: 1. Pollard DA, Bergman CM, Stoye J, Celniker SE, Eisen MB: Benchmarking tools for the alignment of functional noncoding DNA. BMC Bioinformatics 2004, 5:6. 2. Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison RC, Haussler D, Miller W: Human-mouse alignments with BLASTZ. Genome Res 2003, 13:103-7. 3. AlignmentBenchmarking [http://rana.lbl.gov/AlignmentBenchmarking]Peer Reviewe

At Least Bias Is Bipartisan: A Meta-Analytic Comparison of Partisan Bias in Liberals and Conservatives

Both liberals and conservatives accuse their political opponents of partisan bias, but is there empirical evidence that one side of the political aisle is indeed more biased than the other? To address this question, we meta-analyzed the results of 51 experimental studies, involving over 18,000 participants, that examined one form of partisan bias—the tendency to evaluate otherwise identical information more favorably when it supports one’s political beliefs or allegiances than when it challenges those beliefs or allegiances. Two hypotheses based on previous literature were tested: an asymmetry hypothesis (predicting greater partisan bias in conservatives than in liberals) and a symmetry hypothesis (predicting equal levels of partisan bias in liberals and conservatives). Mean overall partisan bias was robust (r = .245), and there was strong support for the symmetry hypothesis: Liberals (r = .235) and conservatives (r = .255) showed no difference in mean levels of bias across studies. Moderator analyses reveal this pattern to be consistent across a number of different methodological variations and political topics. Implications of the current findings for the ongoing ideological symmetry debate and the role of partisan bias in scientific discourse and political conflict are discussed