TAG: Learning Circuit Spatial Embedding From Layouts

Analog and mixed-signal (AMS) circuit designs still rely on human design expertise. Machine learning has been assisting circuit design automation by replacing human experience with artificial intelligence. This paper presents TAG, a new paradigm of learning the circuit representation from layouts leveraging text, self-attention and graph. The embedding network model learns spatial information without manual labeling. We introduce text embedding and a self-attention mechanism to AMS circuit learning. Experimental results demonstrate the ability to predict layout distances between instances with industrial FinFET technology benchmarks. The effectiveness of the circuit representation is verified by showing the transferability to three other learning tasks with limited data in the case studies: layout matching prediction, wirelength estimation, and net parasitic capacitance prediction.Comment: Accepted by ICCAD 202

Cancer-associated exportin-6 upregulation inhibits the transcriptionally repressive and anticancer effects of nuclear profilin-1

Aberrant expression of nuclear transporters and deregulated subcellular localization of their cargo proteins are emerging as drivers and therapeutic targets of cancer. Here, we present evidence that the nuclear exporter exportin-6 and its cargo profilin-1 constitute a functionally important and frequently deregulated axis in cancer. Exportin-6 upregulation occurs in numerous cancer types and is associated with poor patient survival. Reducing exportin-6 level in breast cancer cells triggers antitumor effects by accumulating nuclear profilin-1. Mechanistically, nuclear profilin-1 interacts with eleven-nineteen-leukemia protein (ENL) within the super elongation complex (SEC) and inhibits the ability of the SEC to drive transcription of numerous pro-cancer genes including MYC. XPO6 and MYC are positively correlated across diverse cancer types including breast cancer. Therapeutically, exportin-6 loss sensitizes breast cancer cells to the bromodomain and extra-terminal (BET) inhibitor JQ1. Thus, exportin-6 upregulation is a previously unrecognized cancer driver event by spatially inhibiting nuclear profilin-1 as a tumor suppressor

Characterization of an interplay between a Mycobacterium tuberculosis MazF homolog, Rv1495 and its sole DNA topoisomerase I

The MazEF systems are thought to contribute to the capacity for long-term dormancy observed in the human pathogen, Mycobacterium tuberculosis. However, except for their functions as mRNA interferases, little is known regarding any additional cellular functions of these systems in the pathogen. In the present study, we observed a negative interplay between MazF protein Rv1495 and the sole M. tuberculosis DNA topoisomerase I (MtbTopA) with respect to protein functions. Through its C-terminal domain, MtbTopA physically interacted with and inhibited the mRNA cleavage activity of Rv1495. Rv1495, in turn, inhibited the DNA cleavage activity of MtbTopA as well as its function of relaxation of supercoiled DNA. An N-terminus fragment of Rv1495, designated Rv1495-N(29-56), lost mRNA cleavage activity, but retained a significant physical interaction and inhibitory effect on TopA proteins from both M. tuberculosis and M. smegmatis. This fragment, although less effective than the full-length protein, was able to inhibit mycobacterial growth when expressed through a recombinant plasmid in M. smegmatis. The Rv1495 physically interacted with the M. smegmatis TopA both in vitro and in vivo. Our findings imply that MazEF systems can affect bacterial survival by a novel mechanism that allows direct modulation of M. tuberculosis topoisomerase I

The HicA toxin from Burkholderia pseudomallei has a role in persister cell formation

© 2014 The Authors Journal compilation. ©2014 Biochemical Society.This is an open access article that is freely available in ORE or from the publisher's website. Please cite the published version.Published by Portland Press on behalf of the Biochemical SocietyTA (toxin-antitoxin) systems are widely distributed amongst bacteria and are associated with the formation of antibiotic tolerant (persister) cells that may have involvement in chronic and recurrent disease. We show that overexpression of the Burkholderia pseudomallei HicA toxin causes growth arrest and increases the number of persister cells tolerant to ciprofloxacin or ceftazidime. Furthermore, our data show that persistence towards ciprofloxacin or ceftazidime can be differentially modulated depending on the level of induction of HicA expression. Deleting the hicAB locus from B. pseudomallei K96243 significantly reduced persister cell frequencies following exposure to ciprofloxacin, but not ceftazidime. The structure of HicA(H24A) was solved by NMR and forms a dsRBD-like (dsRNA-binding domain-like) fold, composed of a triple-stranded β-sheet, with two helices packed against one face. The surface of the protein is highly positively charged indicative of an RNA-binding protein and His24 and Gly22 were functionality important residues. This is the first study demonstrating a role for the HicAB system in bacterial persistence and the first structure of a HicA protein that has been experimentally characterized.Wellcome Trus

Key features of the two-intron Saccharomyces cerevisiae gene SUS1 contribute to its alternative splicing

Alternative pre-mRNA splicing allows dramatic expansion of the eukaryotic proteome and facilitates cellular response to changes in environmental conditions. The Saccharomyces cerevisiae gene SUS1, which encodes a protein involved in mRNA export and histone H2B deubiquitination, contains two introns; non-canonical sequences in the first intron contribute to its retention, a common form of alternative splicing in plants and fungi. Here we show that the pattern of SUS1 splicing changes in response to environmental change such as temperature elevation, and the retained intron product is subject to nonsense-mediated decay. The activities of different splicing factors determine the pattern of SUS1 splicing, including intron retention and exon skipping. Unexpectedly, removal of the 3′ intron is affected by splicing of the upstream intron, suggesting that cross-exon interactions influence intron removal. Production of different SUS1 isoforms is important for cellular function, as we find that the temperature sensitivity and histone H2B deubiquitination defects observed in sus1Δ cells are only partially suppressed by SUS1 cDNA, but SUS1 that is able to undergo splicing complements these phenotypes. These data illustrate a role for S. cerevisiae alternative splicing in histone modification and cellular function and reveal important mechanisms for splicing of yeast genes containing multiple introns

Green function techniques in the treatment of quantum transport at the molecular scale

The theoretical investigation of charge (and spin) transport at nanometer length scales requires the use of advanced and powerful techniques able to deal with the dynamical properties of the relevant physical systems, to explicitly include out-of-equilibrium situations typical for electrical/heat transport as well as to take into account interaction effects in a systematic way. Equilibrium Green function techniques and their extension to non-equilibrium situations via the Keldysh formalism build one of the pillars of current state-of-the-art approaches to quantum transport which have been implemented in both model Hamiltonian formulations and first-principle methodologies. We offer a tutorial overview of the applications of Green functions to deal with some fundamental aspects of charge transport at the nanoscale, mainly focusing on applications to model Hamiltonian formulations.Comment: Tutorial review, LaTeX, 129 pages, 41 figures, 300 references, submitted to Springer series "Lecture Notes in Physics

MATS: a Bayesian framework for flexible detection of differential alternative splicing from RNA-Seq data

Ultra-deep RNA sequencing has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We develop MATS (multivariate analysis of transcript splicing), a Bayesian statistical framework for flexible hypothesis testing of differential alternative splicing patterns on RNA-Seq data. MATS uses a multivariate uniform prior to model the between-sample correlation in exon splicing patterns, and a Markov chain Monte Carlo (MCMC) method coupled with a simulation-based adaptive sampling procedure to calculate the P-value and false discovery rate (FDR) of differential alternative splicing. Importantly, the MATS approach is applicable to almost any type of null hypotheses of interest, providing the flexibility to identify differential alternative splicing events that match a given user-defined pattern. We evaluated the performance of MATS using simulated and real RNA-Seq data sets. In the RNA-Seq analysis of alternative splicing events regulated by the epithelial-specific splicing factor ESRP1, we obtained a high RT–PCR validation rate of 86% for differential exon skipping events with a MATS FDR of <10%. Additionally, over the full list of RT–PCR tested exons, the MATS FDR estimates matched well with the experimental validation rate. Our results demonstrate that MATS is an effective and flexible approach for detecting differential alternative splicing from RNA-Seq data