MiRPara: a SVM-based software tool for prediction of most probable microRNA coding regions in genome scale sequences

<p>Abstract</p> <p>Background</p> <p>MicroRNAs are a family of ~22 nt small RNAs that can regulate gene expression at the post-transcriptional level. Identification of these molecules and their targets can aid understanding of regulatory processes. Recently, HTS has become a common identification method but there are two major limitations associated with the technique. Firstly, the method has low efficiency, with typically less than 1 in 10,000 sequences representing miRNA reads and secondly the method preferentially targets highly expressed miRNAs. If sequences are available, computational methods can provide a screening step to investigate the value of an HTS study and aid interpretation of results. However, current methods can only predict miRNAs for short fragments and have usually been trained against small datasets which don't always reflect the diversity of these molecules.</p> <p>Results</p> <p>We have developed a software tool, miRPara, that predicts most probable mature miRNA coding regions from genome scale sequences in a species specific manner. We classified sequences from miRBase into animal, plant and overall categories and used a support vector machine to train three models based on an initial set of 77 parameters related to the physical properties of the pre-miRNA and its miRNAs. By applying parameter filtering we found a subset of ~25 parameters produced higher prediction ability compared to the full set. Our software achieves an accuracy of up to 80% against experimentally verified mature miRNAs, making it one of the most accurate methods available.</p> <p>Conclusions</p> <p>miRPara is an effective tool for locating miRNAs coding regions in genome sequences and can be used as a screening step prior to HTS experiments. It is available at <url>http://www.whiov.ac.cn/bioinformatics/mirpara</url></p

Robust Tickets Can Transfer Better: Drawing More Transferable Subnetworks in Transfer Learning

Transfer learning leverages feature representations of deep neural networks (DNNs) pretrained on source tasks with rich data to empower effective finetuning on downstream tasks. However, the pretrained models are often prohibitively large for delivering generalizable representations, which limits their deployment on edge devices with constrained resources. To close this gap, we propose a new transfer learning pipeline, which leverages our finding that robust tickets can transfer better, i.e., subnetworks drawn with properly induced adversarial robustness can win better transferability over vanilla lottery ticket subnetworks. Extensive experiments and ablation studies validate that our proposed transfer learning pipeline can achieve enhanced accuracy-sparsity trade-offs across both diverse downstream tasks and sparsity patterns, further enriching the lottery ticket hypothesis.Comment: Accepted by DAC 202

NetDistiller: Empowering Tiny Deep Learning via In-Situ Distillation

Boosting the task accuracy of tiny neural networks (TNNs) has become a fundamental challenge for enabling the deployments of TNNs on edge devices which are constrained by strict limitations in terms of memory, computation, bandwidth, and power supply. To this end, we propose a framework called NetDistiller to boost the achievable accuracy of TNNs by treating them as sub-networks of a weight-sharing teacher constructed by expanding the number of channels of the TNN. Specifically, the target TNN model is jointly trained with the weight-sharing teacher model via (1) gradient surgery to tackle the gradient conflicts between them and (2) uncertainty-aware distillation to mitigate the overfitting of the teacher model. Extensive experiments across diverse tasks validate NetDistiller's effectiveness in boosting TNNs' achievable accuracy over state-of-the-art methods. Our code is available at https://github.com/GATECH-EIC/NetDistiller

Aspect sensitivity of polar mesosphere summer echoes observed with the EISCAT VHF radar

The European Incoherent Scatter Scientific Association (EISCAT) Very High Frequency (224 MHz) Radar has been used to investigate the aspect sensitivity of polar mesosphere summer echoes (PMSE) in the period 13–15 July 2010. The aspect sensitivity of PMSE using this radar and at such a high frequency has not been previously reported. Data concerning the aspect sensitivity of PMSE were collected by traversing the antenna beam from the zenith direction, and comparing the received power. Surprisingly, as the intensity received by the oblique beam was often larger than that of the vertical beam, suggesting the presence of tilted dusty plasma layers as a potential cause, a theoretical model was developed to confirm the existence of these layers and their formation process. The experimental results and theoretical model presented help elucidate the structural properties of the possible generation mechanism of strong radar echoes in the polar summer mesosphere region

i-FlatCam: A 253 FPS, 91.49 μ\muJ/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR

We present a first-of-its-kind ultra-compact intelligent camera system, dubbed i-FlatCam, including a lensless camera with a computational (Comp.) chip. It highlights (1) a predict-then-focus eye tracking pipeline for boosted efficiency without compromising the accuracy, (2) a unified compression scheme for single-chip processing and improved frame rate per second (FPS), and (3) dedicated intra-channel reuse design for depth-wise convolutional layers (DW-CONV) to increase utilization. i-FlatCam demonstrates the first eye tracking pipeline with a lensless camera and achieves 3.16 degrees of accuracy, 253 FPS, 91.49 $\mu$J/Frame, and 6.7mm x 8.9mm x 1.2mm camera form factor, paving the way for next-generation Augmented Reality (AR) and Virtual Reality (VR) devices.Comment: Accepted by VLSI 202

Pol III Promoters to Express Small RNAs: Delineation of Transcription Initiation

Pol III promoters such as U6 are commonly used to express small RNAs, including small interfering RNA, short hairpin RNA, and guide RNA, for the clustered regularly interspaced short palindromic repeats genome-editing system. However, whether the small RNAs were precisely expressed as desired has not been studied. Here, using deep sequencing to analyze small RNAs, we show that, for mouse U6 promoter, sequences immediately upstream of the putative initiation site, which is often modified to accommodate the restriction enzyme sites that enable easy cloning of small RNAs, are critical for precise transcription initiation. When the promoter is kept unmodified, transcription starts precisely from the first available A or G within the range of positions −1 to +2. In addition, we show that transcription from another commonly used pol III promoter, H1, starts at multiple sites, which results in variability at the 5′ end of the transcripts. Thus, inaccuracy of 5′ end of small RNA transcripts might be a common problem when using these promoters to express small RNAs based on currently believed concepts. Our study provides general guidelines for minimizing the variability of initiation, thereby enabling more accurate expression of small RNAs

Contribution of Bacillus Isolates to the Flavor Profiles of Vanilla Beans Assessed through Aroma Analysis and Chemometrics

Colonizing Bacillus in vanilla (Vanilla planifolia Andrews) beans is involved in glucovanillin hydrolysis and vanillin formation during conventional curing. The flavor profiles of vanilla beans under Bacillus-assisted curing were analyzed through gas chromatography-mass spectrometry, electronic nose, and quantitative sensory analysis. The flavor profiles were analytically compared among the vanilla beans under Bacillus-assisted curing, conventional curing, and non-microorganism-assisted curing. Vanilla beans added with Bacillus vanillea XY18 and Bacillus subtilis XY20 contained higher vanillin (3.58% ± 0.05% and 3.48% ± 0.10%, respectively) than vanilla beans that underwent non-microorganism-assisted curing and conventional curing (3.09% ± 0.14% and 3.21% ± 0.15%, respectively). Forty-two volatiles were identified from endogenous vanilla metabolism. Five other compounds were identified from exogenous Bacillus metabolism. Electronic nose data confirmed that vanilla flavors produced through the different curing processes were easily distinguished. Quantitative sensory analysis confirmed that Bacillus-assisted curing increased vanillin production without generating any unpleasant sensory attribute. Partial least squares regression further provided a correlation model of different measurements. Overall, we comparatively analyzed the flavor profiles of vanilla beans under Bacillus-assisted curing, indirectly demonstrated the mechanism of vanilla flavor formation by microbes

A sliding-bulge structure at the Dicer processing site of pre-miRNAs regulates alternative Dicer processing to generate 5′-isomiRs

5′-isomiRs expand the repertoire of miRNA targets. However, how they are generated is not well understood. Previously, we showed that for some miRNAs in mammalian cells, Drosha cleaves at multiple sites to generate multiple pre-miRNAs that give rise to multiple 5′-isomiRs. Here, we showed that for some other miRNAs, 5′-isomiRs are generated by alternative Dicer processing. In addition, we showed that in miR-203, alternative Dicer processing is regulated by a conserved sliding-bulge structure at the Dicer processing site, which allows the pre-miRNA molecule to fold into two different structures that are processed differently by Dicer. So far no RNA motif that slides to change conformation and alter a protein–RNA interaction has been reported. Thus, our study revealed a novel RNA motif that regulates 5′-isomiR generation in some miRNAs. It might also contribute to regulating protein–RNA interactions in other biological processes, since it takes only one point mutation to generate the sliding bulge, and there are a large number of different RNAs in the cell

Experimental study on the flame merging and temperature profile produced by two pool fires beneath the curved ceiling

Compared to single-source fires in tunnels, double-source fires may exhibit more intricate flame merging behavior and higher flame burning rates due to their interaction, thereby escalating the risk of fire propagation within the tunnel. In this investigation, a 1:10 scale model of a horseshoe-shaped tunnel test site was deployed to conduct experiments on lateral double-source fires, scrutinizing flame merging behavior, probability prediction models, and temperature characteristics of tunnel ceiling smoke gas by varying the oil pool size and double-source spacing. Findings from the study suggest that flame merging behavior within the tunnel is contingent upon double-source spacing and heat release rate (HRR), manifesting in three distinct forms: complete merging, intermittent merging, and complete separation. Through the introduction of non-dimensional heat release rate and non-dimensional fire source spacing, a piecewise function has been devised to forecast the probability of flame merging for both fire types. Furthermore, a predictive model for the maximum temperature rise along the longitudinal centerline of a horseshoe tunnel was formulated, drawing from established theoretical frameworks