DeepSig: Deep learning improves signal peptide detection in proteins

Motivation: The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Results: Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. Availability and implementation: DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website

The Borrelia afzelii outer membrane protein BAPKO_0422 binds human Factor-H and is predicted to form a membrane-spanning beta-barrel

The deep evolutionary history of the Spirochetes places their branch point early in the evolution of the diderms, before the divergence of the present day Proteobacteria. As a Spirochete, the morphology of the Borrelia cell envelope shares characteristics of both Gram-positive and Gram-negative bacteria. A thin layer of peptidoglycan, tightly associated with the cytoplasmic membrane is surrounded by a more labile outer membrane (OM). This OM is rich in lipoproteins but with few known integral membrane proteins. The OmpA domain is an eight-stranded membrane-spanning β-barrel, highly conserved among the Proteobacteria but so far unknown in the Spirochetes. In the present work we describe the identification of four novel OmpA-like β-barrels from Borrelia afzelii, the most common cause of erythema migrans rash in Europe. Structural characterisation of one these proteins (BAPKO_0422) by small angle X-ray scattering (SAXS) and circular dichroism indicate a compact globular structure rich in β-strand consistent with a monomeric β-barrel. Ab initio molecular envelopes calculated from the scattering profile are consistent with homology models and demonstrate that BAPKO_0422 adopts a peanut shape with dimensions 25 x 45 Å. Deviations from the standard C-terminal signature sequence are apparent; in particular the C-terminal Phe residue commonly found in Proteobacterial OM proteins is replaced by Ile/Leu or Asn. BAPKO_0422 is demonstrated to bind human factor-H and therefore may contribute to immune evasion by inhibition of the complement response. Encoded by chromosomal genes, these proteins are highly conserved between Borrelia subspecies and may be of diagnostic or therapeutic value

Meta-analysis of haplotype-association studies: comparison of methods and empirical evaluation of the literature

<p>Abstract</p> <p>Background</p> <p>Meta-analysis is a popular methodology in several fields of medical research, including genetic association studies. However, the methods used for meta-analysis of association studies that report haplotypes have not been studied in detail. In this work, methods for performing meta-analysis of haplotype association studies are summarized, compared and presented in a unified framework along with an empirical evaluation of the literature.</p> <p>Results</p> <p>We present multivariate methods that use summary-based data as well as methods that use binary and count data in a generalized linear mixed model framework (logistic regression, multinomial regression and Poisson regression). The methods presented here avoid the inflation of the type I error rate that could be the result of the traditional approach of comparing a haplotype against the remaining ones, whereas, they can be fitted using standard software. Moreover, formal global tests are presented for assessing the statistical significance of the overall association. Although the methods presented here assume that the haplotypes are directly observed, they can be easily extended to allow for such an uncertainty by weighting the haplotypes by their probability.</p> <p>Conclusions</p> <p>An empirical evaluation of the published literature and a comparison against the meta-analyses that use single nucleotide polymorphisms, suggests that the studies reporting meta-analysis of haplotypes contain approximately half of the included studies and produce significant results twice more often. We show that this excess of statistically significant results, stems from the sub-optimal method of analysis used and, in approximately half of the cases, the statistical significance is refuted if the data are properly re-analyzed. Illustrative examples of code are given in Stata and it is anticipated that the methods developed in this work will be widely applied in the meta-analysis of haplotype association studies.</p

PENGARUH JOB SECURITY TERHADAP PERSEPSI KESELAMATAN PADA PEKERJA KONSTRUKSI LAPANGAN DI INDUSTRI MINYAK DAN GAS

Construction projects are activities that are prone to work accidents, so work safety management is needed to prevent work accidents. One of the factors that greatly influences the perception of work safety is the job security. The aim of this research is to identify job security factors and safety perceptions and analyze the influence of the relationship between job security and the perception of safety among field workers in the oil and gas industry, especially in the Riau province work area. The respondents were field workers and numbered 106 people. The research methods used are qualitative and quantitative. There were respondents who stated that the implementation of work safety was very high, but several dimensions such as sustainable salary increases were still not good (34.91%) and respondents stated that understanding and implementation of the perception of safety was very high. The results of the linear regression test show that job security has a positive and significant effect on the perception of safety among field construction workers, where job security contributes to the perception of safety by 21.5%. The more workers do not fulfill job security, the less workers will care about the perception of safety which can lead to not creating a good safety climate and increasing work accidentsProyek konstruksi merupakan kegiatan yang rawan terhadap terjadinya kecelakaan kerja, sehingga diperlukannya manajemen keselamatan kerja untuk mencegah terjadinya kecelakaan kerja. Salah satu faktor yang sangat mempengaruhi persepsi keselamatan kerja adalah job security. Tujuan penelitian ini adalah untuk mengidentifikasi faktor-faktor job security dan persepsi keselamatan serta menganalisis pengaruh hubungan job security terhadap persepsi keselamatan pada pekerja konstruksi lapangan di industri minyak dan gas, khususnya di wilayah kerja Provinsi Riau. Responden adalah pada pekerja konstruksi lapangan dan berjumlah 106 orang. Metode penelitian yang digunakan adalah kualitatif dan kuantitatif. Terdapat responden mengungkapkan bahwa penerapan job security sudah sangat tinggi, namun beberapa dimensi seperti kenaikan gaji yang berkelanjutan masih kurang baik (34,91%) dan responden menyatakan bahwa pemahaman dan implementasi terhadap persepsi keselamatan sudah sangat tinggi. Hasil uji regresi linier menunjukkan job security berpengaruh positif dan signifikan terhadap persepsi keselamatan pada pekerja konstruksi lapangan, dimana job security memberikan kontribusi terhadap persepsi keselamatan sebesar 21,5%. Semakin pekerja tidak terpenuhi job security, maka pekerja akan semakin tidak peduli terhadap persepsi keselamatan yang dapat menyebabkan tidak terciptanya iklim keselamatan yang baik dan menimbulkan kecelakaan kerj

The Effectiveness of Concept Maps on Students’ Achievement in Science: A Meta-Analysis

This study aims to evaluate the effectiveness of concept maps on science achievement among elementary and secondary education students, including low-achieving students. A systematic search located 55 studies about concept mapping in science achievement published in peer-reviewed journals and dissertations between 1980 and 2020. We extracted 58 independent standardized mean difference effect sizes from 55 eligible studies involving 5,364 students from Grade 3 to Grade 12 who used concept maps to learn physics/earth science, chemistry, and biology that met the specified design criteria. A random-effects model meta-analysis revealed that the mean effect size was moderate for overall science (g = 0.776). The mean effect sizes varied from moderate to large based on the subject area (g = 0.671 for biology; g = 0.590 for chemistry; g = 1.040 for physics and earth science); these between-groups differences were not statistically significant (p = 0.220). Concept maps were generally associated with increased science learning across several instructional settings, conditions, and methodological features (type of learners, high-income countries, journal publications, and late year of publication). However, we found significant heterogeneity in most subsets. Implications for future research and practice recommendations are discussed

ANALISIS SWOT DAN MARKETING MIX PADA PRODUK KERIPIK TALAS MENTARI-KOE

Bagos Adi Nugroho, Program Studi Teknik Industri S-1, Fakultas Teknologi Industri, Institut Teknologi Nasional Malang, Januari 2024, Analisis SWOT dan marketing Mix (4P) Pada Produk Keripik Talas Mentari-Koe. Dosen Pembimbing: Ir. ST. Salmia L.A, MT dan Drs. Sumanto, M.Si UMKM Mentari-Koe adalah salah satu UMKM produsen keripik talas yang terletak di Selokurung, Desa Kaumrejo, Kecamatan Ngantang, Kabupaten Malang, Jawa Timur dan telah berdiri sejak tahun 2016. Permasalahan yang dihadapi adalah sering tidak mencapai target penjualan dan adanya persaingan sesama produsen keripik talas yang masih satu kecamatan dan pesaing memiliki penjualan yang lebih banyak daripada UMKM MentariKoe. Adapun tujuan pada penelitian ini adalah untuk mengetahui faktor-faktor serta letak kuadran dan strategi pemasaran marketing mix (4P) pada UMKM Mentari-Koe Penelitian ini menggunakan 2 metode yaitu Analisis SWOT dan Analisis Marketing Mix. Analisis SWOT dikatakan sangat bagus karena memaksimalkan faktor-faktor kekuatan dan pemanfaatan peluang yang akhirnya dapat menekan kelemahan serta ancaman yang timbul dan harus dihadapi. Analisis Marketing Mix merupakan satu perangkat yang terdiri dari produk, harga promosi dan distribusi, yang didalamnya akan menentukan tingkat keberhasilan pemasaran dan semua itu ditujukan untuk mendapatkan respon yang diinginkan dari pasar sasaran. Untuk Analisis SWOT dilakukan penyebaran kuisioner yang dimana hasil kuisioner tersebut kemudian akan dilakukan pengujian data menggunakan SPSS jika data valid dan reliabel maka data dapat dikerjakan sesuai dengan metode Analisis SWOT. Analisis Marketing Mix dilakukan dengan melakukan wawancara kepada pemilik UMKM Mentari-Koe dan dapat hasil Analisis SWOT dapat dijadikan acuan atau masukan. Hasil Penilitian yang dilakukan adalah UMKM Mentari-Koe terdapat pada kuadran II. Kuadran II yang berarti UMKM menghadapi berbagai ancaman akan tetapi masih memiliki kekuatan dari segi internal. Maka, strategi yang sesuai dengan kuadran II adalah S.T (Strenghts-Opportunities). Untuk faktor produk (product) memiliki 2 jenis keripik, harga (price) walaupun lebih mahal pihak agen tetap merasa puas dengan produk, tempat (place) kurang strategis karena jauh dari keramaian dan jalan besar dan promosi (promotion) dilakukan secara langsung ke agen serta terdapat peluang untuk mempromosikan dan menjual di e-commerce. Kata kunci : Analisis SWOT, Marketing Mix, Strategi dan bauran pemasara

Implementasi Sumber Daya Penyimpanan Dinamis Pada Cloud

Seiring dengan perkembangan jaman kebutuhan dan ketergantungan manusia terhadap komputer semakin besar seiring pekembangan dunia teknologi modern. Penggunaan komputer sendiri dari berbagai bidang untuk menyelesaikan masalah komputasi dari skala kecil sampai besar. Tidak dapat dipungkiri dengan berkembangnya aplikasi dalam dunia komputer membutuhkan sumber daya yang lebih besar, sehingga kurang efisien apabila hanya dikerjakan dengan sebuah mesin fisik saja. Berbagai cara dilakukan untuk mengatasi masalah ini salah satunya dengan virtualisasi. Dalam penelitian ini dilakukan implementasi manajemen sumber daya penyimpanan dinamis pada Cloud. Virtulasisasi yang digunakan dalam penelitian ini dengan menggunakan virtual box. Penyimpanan dinamis yang digunakan dalam penelitian ini dengan mengimplementasi fitur Logical Volume Management. Hasil dari penelitian ini didapatkan sebuah sistem yang dapat melakukan penambahan kapasitas storage secara dinamis dan otomatis tanpa adanya dOwntime dan rebooting pada sistem

Evaluation of methods for predicting the topology of β-barrel outer membrane proteins and a consensus prediction method

BACKGROUND: Prediction of the transmembrane strands and topology of β-barrel outer membrane proteins is of interest in current bioinformatics research. Several methods have been applied so far for this task, utilizing different algorithmic techniques and a number of freely available predictors exist. The methods can be grossly divided to those based on Hidden Markov Models (HMMs), on Neural Networks (NNs) and on Support Vector Machines (SVMs). In this work, we compare the different available methods for topology prediction of β-barrel outer membrane proteins. We evaluate their performance on a non-redundant dataset of 20 β-barrel outer membrane proteins of gram-negative bacteria, with structures known at atomic resolution. Also, we describe, for the first time, an effective way to combine the individual predictors, at will, to a single consensus prediction method. RESULTS: We assess the statistical significance of the performance of each prediction scheme and conclude that Hidden Markov Model based methods, HMM-B2TMR, ProfTMB and PRED-TMBB, are currently the best predictors, according to either the per-residue accuracy, the segments overlap measure (SOV) or the total number of proteins with correctly predicted topologies in the test set. Furthermore, we show that the available predictors perform better when only transmembrane β-barrel domains are used for prediction, rather than the precursor full-length sequences, even though the HMM-based predictors are not influenced significantly. The consensus prediction method performs significantly better than each individual available predictor, since it increases the accuracy up to 4% regarding SOV and up to 15% in correctly predicted topologies. CONCLUSIONS: The consensus prediction method described in this work, optimizes the predicted topology with a dynamic programming algorithm and is implemented in a web-based application freely available to non-commercial users at

OMPdb: a database of β-barrel outer membrane proteins from Gram-negative bacteria

We describe here OMPdb, which is currently the most complete and comprehensive collection of integral β-barrel outer membrane proteins from Gram-negative bacteria. The database currently contains 69 354 proteins, which are classified into 85 families, based mainly on structural and functional criteria. Although OMPdb follows the annotation scheme of Pfam, many of the families included in the database were not previously described or annotated in other publicly available databases. There are also cross-references to other databases, references to the literature and annotation for sequence features, like transmembrane segments and signal peptides. Furthermore, via the web interface, the user can not only browse the available data, but submit advanced text searches and run BLAST queries against the database protein sequences or domain searches against the collection of profile Hidden Markov Models that represent each family’s domain organization as well. The database is freely accessible for academic users at http://bioinformatics.biol.uoa.gr/OMPdb and we expect it to be useful for genome-wide analyses, comparative genomics as well as for providing training and test sets for predictive algorithms regarding transmembrane β-barrels

Algorithms for incorporating prior topological information in HMMs: application to transmembrane proteins

BACKGROUND: Hidden Markov Models (HMMs) have been extensively used in computational molecular biology, for modelling protein and nucleic acid sequences. In many applications, such as transmembrane protein topology prediction, the incorporation of limited amount of information regarding the topology, arising from biochemical experiments, has been proved a very useful strategy that increased remarkably the performance of even the top-scoring methods. However, no clear and formal explanation of the algorithms that retains the probabilistic interpretation of the models has been presented so far in the literature. RESULTS: We present here, a simple method that allows incorporation of prior topological information concerning the sequences at hand, while at the same time the HMMs retain their full probabilistic interpretation in terms of conditional probabilities. We present modifications to the standard Forward and Backward algorithms of HMMs and we also show explicitly, how reliable predictions may arise by these modifications, using all the algorithms currently available for decoding HMMs. A similar procedure may be used in the training procedure, aiming at optimizing the labels of the HMM's classes, especially in cases such as transmembrane proteins where the labels of the membrane-spanning segments are inherently misplaced. We present an application of this approach developing a method to predict the transmembrane regions of alpha-helical membrane proteins, trained on crystallographically solved data. We show that this method compares well against already established algorithms presented in the literature, and it is extremely useful in practical applications. CONCLUSION: The algorithms presented here, are easily implemented in any kind of a Hidden Markov Model, whereas the prediction method (HMM-TM) is freely available for academic users at , offering the most advanced decoding options currently available