Instruments and Warning Signs for Identifying and Evaluating the Frequency of Adverse Events in Intermediate and Long-Term Care Centres: A Narrative Systematic Review.

INTRODUCTION: There is a lack of data about adverse events (AE) in intermediate and long-term care centers (ILCC). We aimed to synthesize the available scientific evidence on instruments used to identify and characterize AEs. We also aimed to describe the most common adverse events in ILCCs. MATERIAL AND METHODS: A narrative systematic review of the literature was conducted according to Prisma recommendations. The PubMed database was searched for articles published between 2000 and 2021. Two reviewers independently screened and reviewed the studies through blind and independent review. We evaluated bias risk with Cochrane's risk of bias tool. Disagreements were resolved by consensus. Discrepancies that were not resolved by discussion were discussed with a third reviewer. Descriptive data was extracted and qualitative content analysis was performed. RESULTS: We found 2191 articles. Based on the inclusion and exclusion criteria, 272 papers were screened by title and abstract, and 66 studies were selected for full review. The instruments used to identify AEs were mostly tools to identify specific AEs or risks of AEs (94%), the remaining 6% were multidimensional. The most frequent categories detected medication-related AEs (n=26, 40%); falls (n=7, 11%); psychiatric AEs (6.9%); malnutrition (4.6%), and infections (4.6%). The studies that used multidimensional tools refer to frailty, dependency, or lack of energy as predictors of AEs. However, they do not take into account the importance of detecting AEs. We found 2-11 adverse drug events (ADE) per resident/month. We found a prevalence of falls (12.5%), delirium (9.6-89%), pain (68%), malnutrition (2-83%), and pressure ulcers (3-30%). Urinary tract infections, lower respiratory tract infections, skin and soft tissue infections, and gastroenteritis were the most common infections in this setting. Transitions between different care settings (from hospitals to ILCC and vice versa) expose AE risk. CONCLUSION: There are many instruments to detect AEs in ILCC, and most have a specific approach. Adverse events affect a significant proportion of patients in ILCC, the nurse-sensitive outcomes, nosocomial infections, and adverse drug events are among the most common. The systematic review was registered with Prospero, ID: CRD42022348168.

Droplet digital PCR as a tool to detect resistant isolates of Dirofilaria immitis.

Prevention of canine heartworm disease, caused by Dirofilaria immitis, relies on macrocyclic lactones for which drug resistance is now a concern. Although genetic polymorphisms have been associated with resistance in D. immitis populations, the mechanism is still not well understood. The lack of reliable in vitro assays to detect resistance is a limitation for confirming resistance. Ten single nucleotide polymorphisms (SNPs) were previously clinically validated in D. immitis resistant isolates, using the MiSeq platform. This technique although useful for research studies is expensive and does not facilitate rapid detection of these markers in small numbers of clinical samples. We developed a droplet digital PCR protocol for detecting SNPs correlating with ML resistance. Specific primers and hydrolysis probes encompassing the wildtype and mutant alleles were designed to amplify the SNP targets from genomic DNA of different D. immitis isolates. Allele frequencies were determined and the suitability of the ddPCR assay was assessed and compared with MiSeq data. The ddPCR assay accurately detected and quantified alternate nucleotides in two isolates of reference, the ML-susceptible Missouri (MO) and ML-resistant JYD-34, at the previously identified SNP positions. The presence of the SNPs was also determined in additional isolates with known or putative susceptible or resistant phenotypes. We observed SNP1 and SNP2 are more predictive markers and appear suitable for rapid detection and monitoring of drug resistance. Our results suggested that ddPCR could be employed to distinguish infection due to actual genetic resistance from infection with susceptible parasites and also for rapid detection of isolates not only with ML susceptible and resistant genotypes but also mixed genotypes that correspond to heterogeneous isolates containing a mixed population of ML susceptible and resistant parasites. DdPCR may be a useful tool for conducting surveys, or assessments of individual isolates, for genetic evidence of resistance or developing resistance.

MASTR Pouch: Palm-size lab for point-of-care detection of Mpox using recombinase polymerase amplification and CRISPR technology.

Mpox (formerly referred as Monkeypox) outbreak has been declared a Public Health Emergency of International Concern. However, traditional polymerase chain reaction (PCR) diagnostic technology is not ideal for on-site applications. To conduct the sample-to-result Mpox viral particles detection outside the laboratories, we developed an easy-to-operate palm-size pouch, termed Mpox At-home Self-Test and point-of-caRe Pouch (MASTR Pouch). In this MASTR Pouch, the fast and accurate visualization was achieved by incorporating recombinase polymerase amplification (RPA) with clustered regularly interspaced short palindromic repeat (CRISPR)/Cas12a system. From viral particle lysis to naked eye readout, MASTR Pouch required only four simple steps to accomplish the analysis process within 35 min. Fifty-three Mpox pseudo-viral particles in exudate (10.6 particles/µL) were able to be detected. To verify the practicability, 104 mock Mpox clinical exudate specimens were tested. The clinical sensitivities were determined to be 91.7%- 95.8%. There was no false-positive result, validating the 100% clinical specificity. MASTR Pouch approaches the WHO's ASSURD criteria for point-of-care diagnostic, which will be beneficial for mitigating Mpox's global spread. The versatility potential of MASTR Pouch could further revolutionize infection diagnosis.

Immunohistochemistry as a detection tool for ion channels involved in dental pain signaling.

Background: Despite advances in pain detection, diagnosis, and management, the prevalence of dental pain is still on the rise. Although dental pain is not directly related to fatal outcomes, the two most common types of dental pain-dental caries and dentin hypersensitivity-have a significant impact on an individual's quality of life. Understanding the mechanism of the pain pathway is one of the crucial steps in providing better treatment for these patients. Ion channels are critical biomolecules that have been the subject of dental study owing to their roles in the transmission and transduction of external stimuli, as well as in the control and perception of pain. Numerous immunohistochemical (IHC) staining approaches have also been used to identify the many ion channels implicated in peripheral pain signaling in dental pulp. Highlight: This review highlights the critical steps in IHC and its role in the detection of ion channels involved in the dental pain signaling pathway. Conclusion: The key ion channels identified using IHC and whose functions have been widely researched in dental tissues are addressed in this review article.

Why secret detection tools are not enough: It's not just about false positives - An industrial case study.

Checked-in secrets in version-controlled software projects pose security risks to software and services. Secret detection tools can identify the presence of secrets in the code, commit changesets, and project version control history. As these tools can generate false positives, developers are provided with mechanisms to bypass the warnings generated from these tools. Providing this override mechanism can result in developers sometimes exposing secrets in software repositories. The goal of this article is to aid software security practitioners in understanding why' secrets are checked into repositories, despite being warned by tools, through an industrial case study of analysis of usage data of a secret detection tool and a survey of developers who bypassed the tool alert. In this case study, we analyzed the usage data of a checked-in secret detection tool used widely by a software company and we surveyed developers who bypassed the warnings generated by the tool. From the case study, we found that, despite developers classified 50% of the warning as false positive, developers also bypassed the warning due to time constraints, working with non-shipping projects, technical challenges of eliminating secrets completely from the version control history, technical debts, and perceptions that check-ins are low risk. We advocate practitioners and researchers to investigate the findings of our study further to improve secret detection tools and related development practices. We also advocate that organizations should insert secondary checks, as is done by the company we studied, to capture occasions where developers incorrectly bypass secret detection tools.

A systematic literature review on the current detection tools for authentication analysis of cosmetic ingredients.

BACKGROUND: The use of cosmetic products is considered a necessity for beautification in our daily lives. Cosmetic products composed of natural oils or fats as a main ingredient for various beneficial properties. Fats and oils are composed of various type of fatty acids with different compositions. Hence, fatty acids profile can be an effective chemical fingerprint for authentication analysis of cosmetic products. OBJECTIVE: This systematic review aims to enlighten the current detection tools developing for fatty acids profile authentication analyses of cosmetic ingredients based on the effectiveness, halal status, safety, advantages and disadvantages of the methods. METHODOLOGY: The data were extracted from the scientific literatures published between October 2015 and 2020 in the Web of Science, Scopus and Google Scholar databases, and analyzed with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). FINDINGS: Based on the systemic literature reviews, essential oil, argan oil, mineral oil, vegetable oil, and jojoba oil were among the mostly studied ingredients in cosmetics. Furthermore, a combination of more than one analytical instrument was utilized to profile fatty acids while the determination of the origin of the fatty acids is under scrutiny. The portable mass spectrometer combined with a direct inlet membrane (DIM) probe seems to be the best tool in terms of time consumption, cost, requires no sample preparation with high efficiency. The current review showed that the best cosmetic base is when the oil is composed of high concentration of fatty acids such as linoleic, oleic, stearic acid, and palmitic acids with concentration range from 19.7 - 46.30%, which offers various beneficial properties to cosmetic products.

Applications of Adductomics in Chemically Induced Adverse Outcomes and Major Emphasis on DNA Adductomics: A Pathbreaking Tool in Biomedical Research.

Adductomics novel and emerging discipline in the toxicological research emphasizes on adducts formed by reactive chemical agents with biological molecules in living organisms. Development in analytical methods propelled the application and utility of adductomics in interdisciplinary sciences. This review endeavors to add a new dimension where comprehensive insights into diverse applications of adductomics in addressing some of society's pressing challenges are provided. Also focuses on diverse applications of adductomics include: forecasting risk of chronic diseases triggered by reactive agents and predicting carcinogenesis induced by tobacco smoking; assessing chemical agents' toxicity and supplementing genotoxicity studies; designing personalized medication and precision treatment in cancer chemotherapy; appraising environmental quality or extent of pollution using biological systems; crafting tools and techniques for diagnosis of diseases and detecting food contaminants; furnishing exposure profile of the individual to electrophiles; and assisting regulatory agencies in risk assessment of reactive chemical agents. Characterizing adducts that are present in extremely low concentrations is an exigent task and more over absence of dedicated database to identify adducts is further exacerbating the problem of adduct diagnosis. In addition, there is scope of improvement in sample preparation methods and data processing software and algorithms for accurate assessment of adducts.

Cultural Adaptation of Community Informant Tool for Detection of Maternal Depression in Rural Pakistan.

Background: Evidence indicates that mental health issues like depression, epilepsy, and substance misuse can be detected with reasonable accuracy in resource-poor settings. The Community Informant Detection Tool (CIDT) is one such approach used for detecting mental health problems, including depression. We adapted this community informant approach for detecting maternal depression in Pakistan. Methods: Adaptation of Community Informant Detection Tool for Maternal Depression (CIDT-MD) involved five steps. First, a scoping review of the literature was conducted to select an appropriate tool for adaptation. Second, in-depth interviews were conducted to explore the idioms of depression and distress, perceived causes, and the effects of maternal depression among currently depressed and recovered mothers (n = 11), mothers in law (n = 6), and Primary Care Providers (Primary Care Physicians and Lady Health Supervisors) (n = 6). Third, case vignettes and illustrations were created with input from a panel of mental health experts, incorporating the idioms of depression and distress used, causes, and effects for each symptom described. Fourth, to assess the comprehensibility of the illustrations and level of understanding, Focus Group Discussions (n = 4) were done with purposely selected community health workers (Lady Health Workers and Lay Peers, n = 28) trained in delivering maternal depression intervention. The final step was reflection and inputs by a panel of mental health experts on all steps to finalize the content of the tool. Results: Context-specific cultural adaptation in the presentation and format of CIDT-MD was conducted successfully. Lady Health Workers (LHW) and Lay Peers (LP) were found to be the most appropriate persons to use the tool and function as the informants. The adapted tool with all its vignettes and illustrations was found to be easily understandable, comprehensible, and culturally appropriate, meaningful, and contextually relevant by the community health workers and peers working in the relevant settings. They easily relate to and identify potentially depressed such women lining up with the tool. Lastly, the coding of the tool was found easy to follow as well. Conclusion: The Community Informant Detection Tool for Maternal Depression (CIDT-MD) is a culturally acceptable, easy to use, and comprehensible tool for detecting maternal depression in community settings of Pakistan. The community informants found the content and approach highly relevant to the local needs.

Characterization of PlyB221 and PlyP32, Two Novel Endolysins Encoded by Phages Preying on the Bacillus cereus Group.

Endolysins are phage-encoded enzymes implicated in the breaching of the bacterial cell wall at the end of the viral cycle. This study focuses on the endolysins of Deep-Blue (PlyB221) and Deep-Purple (PlyP32), two phages preying on the Bacillus cereus group. Both enzymes exhibit a typical modular organization with an enzymatically active domain (EAD) located in the N-terminal and a cell wall binding domain (CBD) in the C-terminal part of the protein. In silico analysis indicated that the EAD domains of PlyB221 and PlyP32 are endowed with peptidase and muramidase activities, respectively, whereas in both proteins SH3 domains are involved in the CBD. To evaluate their antimicrobial properties and binding specificity, both endolysins were expressed and purified. PlyB221 and PlyP32 efficiently recognized and lysed all the tested strains from the B. cereus group. Biochemical characterization showed that PlyB221 activity was stable under a wide range of pHs (5-9), NaCl concentrations (up to 200 mM), and temperature treatments (up to 50 °C). Although PlyP32 activity was less stable than that of PlyB221, the endolysin displayed high activity at pH 6-7, NaCl concentration up to 100 mM and the temperature treatment up to 45 °C. Overall, PlyB221 and PlyP32 display suitable characteristics for the development of biocontrol and detection tools.

Severity detection tool for patients with infectious disease.

Hand foot and mouth disease (HFMD) and tetanus are serious infectious diseases in low- and middle-income countries. Tetanus, in particular, has a high mortality rate and its treatment is resource-demanding. Furthermore, HFMD often affects a large number of infants and young children. As a result, its treatment consumes enormous healthcare resources, especially when outbreaks occur. Autonomic nervous system dysfunction (ANSD) is the main cause of death for both HFMD and tetanus patients. However, early detection of ANSD is a difficult and challenging problem. The authors aim to provide a proof-of-principle to detect the ANSD level automatically by applying machine learning techniques to physiological patient data, such as electrocardiogram waveforms, which can be collected using low-cost wearable sensors. Efficient features are extracted that encode variations in the waveforms in the time and frequency domains. The proposed approach is validated on multiple datasets of HFMD and tetanus patients in Vietnam. Results show that encouraging performance is achieved. Moreover, the proposed features are simple, more generalisable and outperformed the standard heart rate variability analysis. The proposed approach would facilitate both the diagnosis and treatment of infectious diseases in low- and middle-income countries, and thereby improve patient care.

Colloidal gold-based immunochromatographic strip assay for the rapid detection of bacitracin zinc in milk.

In this study, a murine monoclonal antibody (mAb) of 6D2-G10 against bacitracin zinc (BAC) was produced and applied to an immunochromatographic strip (ICS) for the initial detection of BAC in milk. The ICS with a cut-off value of 25 ng/mL could be perceived by the naked eye within 10 min. With the assist of the strip reader, the limit of detection (LOD) was measured as 0.82 ng/mL, the half-maximal inhibitory concentration (IC50) was recorded as 3.16 ng/mL, and the linear detection range was from 0.97 to 10.30 ng/mL. The recoveries ranged from 87.7% to 96.0% with the highest coefficient of variation (CV) of 9.1% in the intra-assay and from 84.3% to 90.2% with the highest CV of 10.7% in the inter-assay. In short, the established ICS provided a serviceable analytical tool for qualitatively and quantitatively monitoring BAC in milk.

Hierarchical discovery of large-scale and focal copy number alterations in low-coverage cancer genomes.

BACKGROUND: Detection of DNA copy number alterations (CNAs) is critical to understand genetic diversity, genome evolution and pathological conditions such as cancer. Cancer genomes are plagued with widespread multi-level structural aberrations of chromosomes that pose challenges to discover CNAs of different length scales, and distinct biological origins and functions. Although several computational tools are available to identify CNAs using read depth (RD) signal, they fail to distinguish between large-scale and focal alterations due to inaccurate modeling of the RD signal of cancer genomes. Additionally, RD signal is affected by overdispersion-driven biases at low coverage, which significantly inflate false detection of CNA regions. RESULTS: We have developed CNAtra framework to hierarchically discover and classify 'large-scale' and 'focal' copy number gain/loss from a single whole-genome sequencing (WGS) sample. CNAtra first utilizes a multimodal-based distribution to estimate the copy number (CN) reference from the complex RD profile of the cancer genome. We implemented Savitzky-Golay smoothing filter and Modified Varri segmentation to capture the change points of the RD signal. We then developed a CN state-driven merging algorithm to identify the large segments with distinct copy numbers. Next, we identified focal alterations in each large segment using coverage-based thresholding to mitigate the adverse effects of signal variations. Using cancer cell lines and patient datasets, we confirmed CNAtra's ability to detect and distinguish the segmental aneuploidies and focal alterations. We used realistic simulated data for benchmarking the performance of CNAtra against other single-sample detection tools, where we artificially introduced CNAs in the original cancer profiles. We found that CNAtra is superior in terms of precision, recall and f-measure. CNAtra shows the highest sensitivity of 93 and 97% for detecting large-scale and focal alterations respectively. Visual inspection of CNAs revealed that CNAtra is the most robust detection tool for low-coverage cancer data. CONCLUSIONS: CNAtra is a single-sample CNA detection tool that provides an analytical and visualization framework for CNA profiling without relying on any reference control. It can detect chromosome-level segmental aneuploidies and high-confidence focal alterations, even from low-coverage data. CNAtra is an open-source software implemented in MATLAB®. It is freely available at https://github.com/AISKhalil/CNAtra.

Is there plagiarism in the most influential publications in the field of andrology?

Plagiarism is a common form of academic misconduct that extensively jeopardises the quality of scientific publication. The purpose of this study is to determine the extent of plagiarism in the most influential andrology articles. A total of 77 highly cited andrology articles were analysed for their similarity index using iThenticate and Turnitin. The articles were categorised based on the year (before and on/after 2000) and type of publication (review and research articles), and the similarity indices were compared. Furthermore, the analysed articles were categorised based on the level of similarity using an arbitrary similarity index range (low: ≤10, moderate: 11-20, high: 21-50 and very high: >50) and average incidence rate (%) was determined. Our analysis revealed a higher percentage of the similarity indices for reviews than research articles. We noticed a higher similarity index for articles published on/after 2000 than those published before. The majority of the influential articles in the field of andrology showed a low similarity index, while some articles exhibited moderate to high levels of similarity. These findings support the need for the development of similarity index guidelines as a major pre-requisite for establishing a more transparent and efficient system to address plagiarism in scientific publications.

Translation and perceptions of the French version of the Cancer Survivor Profile-Breast Cancer (CSPro-BC): a tool to identify and manage unmet needs.

PURPOSE: Worldwide healthcare systems continue to struggle to reduce the unmet needs of a growing population of breast cancer survivors (BCSs). The Cancer Survivor Profile-Breast Cancer (CSPro-BC) survey was developed to address BCS's specific needs. This study aims to produce a culturally adapted French version of the CSPro-BC. METHODS: The CSPro-BC(French) was developed through five steps including back translation, use of a multidisciplinary committee, and pretest with BCS (n = 22). Healthcare providers (HCP) (n = 7) from cancer and primary care settings were also interviewed to obtain perceptions of facilitators and barriers to utilization in daily practice. RESULTS: BCS were 40-69 years old (50%), ≥ 5 years post-diagnosis (45%), received chemotherapy alone or in combination (73%). Questionnaire instructions were perceived as clear, the number of questions (n = 73) acceptable, the questions non-intrusive and not complicated. Clarity of questions (min = 1; max = 7) ranged from 4 to 7 with a mean score of 5.9 out of 7. HCP perceived the CSPro-BC(French) as useful for improving communication with BCS. However, HCP stressed implementation concerns regarding competencies, BCS acceptability, and limited resources in the healthcare system to meet the identified concerns. CONCLUSIONS: CSPro-BC(French) is a credible tool for assessment in Francophone nations. Our study provides an important perspective in the translation method, including both survivors and HCP perspectives. Further research is required to evaluate its psychometric qualities, sensitivity to change and its clinical signification. IMPLICATIONS FOR CANCER SURVIVORS: Access to assessment tools specific to French-speaking cancer survivors having a potential to improve support from HCP and self-management capacity for BCS.

Performance evaluation for MOTIFSIM.

BACKGROUND: Previous studies show various results obtained from different motif finders for an identical dataset. This is largely due to the fact that these tools use different strategies and possess unique features for discovering the motifs. Hence, using multiple tools and methods has been suggested because the motifs commonly reported by them are more likely to be biologically significant. RESULTS: The common significant motifs from multiple tools can be obtained by using MOTIFSIM tool. In this work, we evaluated the performance of MOTIFSIM in three aspects. First, we compared the pair-wise comparison technique of MOTIFSIM with the un-gapped Smith-Waterman algorithm and four common distance metrics: average Kullback-Leibler, average log-likelihood ratio, Chi-Square distance, and Pearson Correlation Coefficient. Second, we compared the performance of MOTIFSIM with RSAT Matrix-clustering tool for motif clustering. Lastly, we evaluated the performances of nineteen motif finders and the reliability of MOTIFSIM for identifying the common significant motifs from multiple tools. CONCLUSIONS: The pair-wise comparison results reveal that MOTIFSIM attains better performance than the un-gapped Smith-Waterman algorithm and four distance metrics. The clustering results also demonstrate that MOTIFSIM achieves similar or even better performance than RSAT Matrix-clustering. Furthermore, the findings indicate if the motif detection does not require a special tool for detecting a specific type of motif then using multiple motif finders and combining with MOTIFSIM for obtaining the common significant motifs, it improved the results for DNA motif detection.

MODSIDE: a motif discovery pipeline and similarity detector.

BACKGROUND: Previous studies demonstrate the usefulness of using multiple tools and methods for improving the accuracy of motif detection. Over the past years, numerous motif discovery pipelines have been developed. However, they typically report only the top ranked results either from individual motif finders or from a combination of multiple tools and algorithms. RESULTS: Here we present MODSIDE, a motif discovery pipeline and similarity detector. The pipeline integrated four de novo motif finders: ChIPMunk, MEME, Weeder, and XXmotif. It also incorporated a motif similarity detection tool MOTIFSIM. MODSIDE was designed for delivering not only the predictive results from individual motif finders but also the comparison results for multiple tools. The results include the common significant motifs from multiple tools, the motifs detected by some tools but not by others, and the best matches for each motif in the motif collection of multiple tools. MODSIDE also possesses other useful features for merging similar motifs and clustering motifs into motif trees. CONCLUSIONS: We evaluated MODSIDE and its adopted motif finders on 16 benchmark datasets. The statistical results demonstrate MODSIDE achieves better accuracy than individual motif finders. We also compared MODSIDE with two popular motif discovery pipelines: MEME-ChIP and RSAT peak-motifs. The comparison results reveal MODSIDE attains similar performance as RSAT peak-motifs but better accuracy than MEME-ChIP. In addition, MODSIDE is able to deliver various comparison results that are not offered by MEME-ChIP, RSAT peak-motifs, and other existing motif discovery pipelines.

Drawing what lies ahead: False intentions are more abstractly depicted than true intentions.

The aim of this study was to examine how people mentally represent and depict true and false statements about claimed future actions-so-called true and false intentions. On the basis of construal level theory, which proposes that subjectively unlikely events are more abstractly represented than likely ones, we hypothesized that false intentions should be represented at a more abstract level than true intentions. Fifty-six hand drawings, produced by participants to describe mental images accompanying either true or false intentions, were rated on level of abstractness by a second set of participants (N = 117) blind to the veracity of the intentions. As predicted, drawings of false intentions were rated as more abstract than drawings of true intentions. This result advances the use of drawing-based deception detection techniques to the field of true and false intentions and highlights the potential for abstractness as a novel cue to deceit.

dbGAPs: A comprehensive database of genes and genetic markers associated with psoriasis and its subtypes.

Psoriasis is a systemic hyperproliferative inflammatory skin disorder, although rarely fatal but significantly reduces quality of life. Understanding the full genetic component of the disease association may provide insight into biological pathways as well as targets and biomarkers for diagnosis, prognosis and therapy. Studies related to psoriasis associated genes and genetic markers are scattered and not easily amendable to data-mining. To alleviate difficulties, we have developed dbGAPs an integrated knowledgebase representing a gateway to psoriasis associated genomic data. The database contains annotation for 202 manually curated genes associated with psoriasis and its subtypes with cross-references. Functional enrichment of these genes, in context of Gene Ontology and pathways, provide insight into their important role in psoriasis etiology and pathogenesis. The dbGAPs interface is enriched with an interactive search engine for data retrieval along with unique customized tools for Single Nucleotide Polymorphism (SNP)/indel detection and SNP/indel annotations. dbGAPs is accessible at http://www.bmicnip.in/dbgaps/.

MOTIFSIM 2.1: An Enhanced Software Platform for Detecting Similarity in Multiple DNA Motif Data Sets.

Finding binding site motifs plays an important role in bioinformatics as it reveals the transcription factors that control the gene expression. The development for motif finders has flourished in the past years with many tools have been introduced to the research community. Although these tools possess exceptional features for detecting motifs, they report different results for an identical data set. Hence, using multiple tools is recommended because motifs reported by several tools are likely biologically significant. However, the results from multiple tools need to be compared for obtaining common significant motifs. MOTIFSIM web tool and command-line tool were developed for this purpose. In this work, we present several technical improvements as well as additional features to further support the motif analysis in our new release MOTIFSIM 2.1.