Positional weight matrices have sufficient prediction power for analysis of noncoding variants

The commonly accepted model to quantify the specificity of transcription factor binding to DNA is the position weight matrix, also called the position-specific scoring matrix. Position weight matrices are used in thousands of projects and computational tools in regulatory genomics, including prediction of the regulatory potential of single-nucleotide variants. Yet, recently Yan et al. presented new experimental method for analysis of regulatory variants and, based on its results, reported that "the position weight matrices of most transcription factors lack sufficient predictive power". Here, we re-analyze the rich experimental dataset obtained by Yan et al. and show that appropriately selected position weight matrices in fact can successfully quantify transcription factor binding to alternative alleles.

Comparison of Heuristic Priority Rules in the Solution of the Resource-Constrained Project Scheduling Problem

Resource-constrained project scheduling (RCPS) aims to minimize project duration under limited resource availabilities. The heuristic methods that are often used to solve the RCPS problem make use of different priority rules. The comparative merits of different priority rules have not been discussed in the literature in sufficient detail. This study is a response to this research gap. It compares 17 heuristic priority rules and seeks the best performing heuristic priority rule. This is the first study ever that compares heuristic priority rules by considering combinations of variations in (1) resource allocation procedures, (2) number of activities, (3) number of resource constraints, and (4) resource supply levels. The objective is to understand the relative merits of heuristic rules used in solving the RCPS problem. The findings indicate that the “minimum late finish time” rule generates the shortest predicted project duration when used in parallel resource allocation, whereas the “minimum late start time”, “minimum late finish time”, and the “highest rank of positional weight 2” rules perform best in serial resource allocation. It was also found that parallel resource allocation is slightly superior to serial resource allocation in most instances.

Application of alternative de novo motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites

The most popular model for the search of ChIP-seq data for transcription factor binding sites (TFBS) is the positional weight matrix (PWM). However, this model does not take into account dependencies between nucleotide occurrences in different site positions. Currently, two recently proposed models, BaMM and InMoDe, can do as much. However, application of these models was usually limited only to comparing their recognition accuracies with that of PWMs, while none of the analyses of the co-prediction and relative positioning of hits of different models in peaks has yet been performed. To close this gap, we propose the pipeline called MultiDeNA. This pipeline includes stages of model training, assessing their recognition accuracy, scanning ChIP-seq peaks and their classif ication based on scan results. We applied our pipeline to 22 ChIP-seq datasets of TF FOXA2 and considered PWM, dinucleotide PWM (diPWM), BaMM and InMoDe models. The combination of these four models allowed a signif icant increase in the fraction of recognized peaks compared to that for the sole PWM model: the increase was 26.3 %. The BaMM model provided the main contribution to the recognition of sites. Although the major fraction of predicted peaks contained TFBS of different models with coincided positions, the medians of the fraction of peaks containing the predictions of sole models were 1.08, 0.49, 4.15 and 1.73 % for PWM, diPWM, BaMM and InMoDe, respectively. Thus, FOXA2 BSs were not fully described by only a sole model, which indicates theirs heterogeneity. We assume that the BaMM model is the most successful in describing the structure of the FOXA2 BS in ChIP-seq datasets under study.

ANALISA LINE BALANCING MENGGUNAKAN METODE MOODIE YOUNG DAN RANKED POSITIONAL WEIGHT DI CV. XYZ

CV. XYZ adalah perusahaan manufaktur yang bergerak dibidang produksi sarana prasarana lalu lintas seperti RPPJ, PJU, rambu-rambu, dan trafic light. Masalah yang timbul pada perusahaan ini adalah kurang efisiennya lini produksi tiang Rambu Pendahulu Penunjuk Jurusan (RPPJ), yang ditandai dengan munculnya waktu delay yang menyebabkan bottleneck pada sejumlah stasiun kerja. Hal ini disebabkan oleh tidak seimbangnya pembagian beban kerja pada setiap stasiun. Tujuan dari penelitian ini adalah meningkatkan efisiensi lini produksi dengan pendekatan keseimbangan lintasan. Keseimbangan lintasan mampu meningkatkan efisiensi dengan pemerataan beban kerja disetiap stasiun. Metode yang digunakan untuk menyelesaikan permasalahan yaitu Moodie Young dan Ranked Positional Weight. Kedua metode ini memiliki karakteristik yang serupa dalam menyelesaikan permasalahan keseimbangan lintasan, yaitu dengan penggunaan matriks hubungan antar elemen kerja. Hasil perbandingan metode akan dipilih berdasarkan tingkat efisiensi dan smoothes index terbaik sebagai solusi dari permasalahan keseimbangan lintasan. Hasil dari penelitian ini adalah penggunaan metode Moodie Young sebagai solusi optimal, karena memiliki line efficiency sebesar 85,06%, balance delay sebesar 14,94%, dan smoothes index sebesar 47,51, dengan jumlah stasiun kerja sebanyak 9 stasiun kerja. CV.XYZ is a manufacturing company engaged in the production of traffic infrastructure such as RPPJ, PJU, signs, and traffic light. The problem that arises in this company is the inefficient production of the Traffic Direction Sign (RPPJ) pole line production, which is characterized by the emergence of time delays that cause bottlenecks at a number of work stations. This is caused by the unequal distribution of workload at each station. The purpose of this study is to improve the efficiency of the production line with the line balancing approach. Line balancing can increase efficiency by equalizing workload at each station. The methods used to solve the problem are Moodie Young and Ranked Positional Weight. Both of these methods have similar characteristics in solving the problem of line balancing, namely by using a matrix of relationships between work elements. The results of the method comparison will be chosen based on the best level of efficiency and smoothes index as a solution to the problem of line balancing. The results of this study are the use of the Moodie Young method as an optimal solution, because it has a line efficiency of 85.06%, a balance delay of 14.94%, and a smoothes index of 47.51, with a total of 9 work stations.

Line Balancing Analysis of Hollow Dakota 1730 Manufacturing Process in PT XYZ

The existence of operational balance in each production lines may decrease the idle time; it shows that the productivity is increasing therefore it increases the production rate. The issues existed in the production process of hollow Dakota 1730 in PT. XYZ were 3 departments, from the result of the first observation, there was a bottleneck from each department and each production did not achieve the required target. Therefore, this research would fix the production line. The method used was ranked /positional weight. Based on the data processing by the ranked positional weight method, gained the total of work station in the production process of hollow Dakota 1730 by the number of 2 work stations. From the result of efficiency balancing, gained 62.5% and balance delay value was 37.5%. it shows that the balance performance between each department increases significantly.

Motto: Representing Motifs in Consensus Sequences with Minimum Information Loss

Sequence analysis frequently requires intuitive understanding and convenient representation of motifs. Typically, motifs are represented as position weight matrices (PWMs) and visualized using sequence logos. However, in many scenarios, in order to interpret the motif information or search for motif matches, it is compact and sufficient to represent motifs by wildcard-style consensus sequences (such as [GC][AT]GATAAG[GAC]). Based on mutual information theory and Jensen-Shannon divergence, we propose a mathematical framework to minimize the information loss in converting PWMs to consensus sequences. We name this representation as sequence Motto and have implemented an efficient algorithm with flexible options for converting motif PWMs into Motto from nucleotides, amino acids, and customized characters. We show that this representation provides a simple and efficient way to identify the binding sites of 1156 common transcription factors (TFs) in the human genome. The effectiveness of the method was benchmarked by comparing sequence matches found by Motto with PWM scanning results found by FIMO. On average, our method achieves a 0.81 area under the precision-recall curve, significantly (P-value < 0.01) outperforming all existing methods, including maximal positional weight, Cavener’s method, and minimal mean square error. We believe this representation provides a distilled summary of a motif, as well as the statistical justification.

Analysis and Improvement of Assembly Line: A Case Study at Automobile Rear-Axle Assembly Line-A PT. ZYX

This paper explains the improvement of PT ZYX's productivity on the assembly line-A, using the production line balancing method. Four methods of line balancing were examined, namely, Ranking Positional Weight (RPW), Region Approach, J-Wagon and Kaizen. The selection of the most suitable method is made based on the reduction of number of workstation and cycle-time. Based on the result. Kaizen method shows better total cycle time, number of workstation, and number of operator required. This result is simulated using the 'Tecnomatix' software with the DES (Discrete Event Simulation) method.