Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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maTE: discovering expressed interactions between microRNAs and their targets
Yousef, Malik ; Abddallah, Loai ; Allmer, Jens - \ 2019
Bioinformatics 35 (2019)20. - ISSN 1367-4803 - p. 4020 - 2028.
Motivation

Disease is often manifested via changes in transcript and protein abundance. MicroRNAs (miRNAs) are instrumental in regulating protein abundance and may measurably influence transcript levels. MicroRNAs often target more than one mRNA (for humans, the average is three), and mRNAs are often targeted by more than one miRNA (for the genes considered in this study, the average is also three). Therefore, it is difficult to determine the miRNAs that may cause the observed differential gene expression.

We present a novel approach, maTE, which is based on machine learning, that integrates information about miRNA target genes with gene expression data. maTE depends on the availability of a sufficient amount of patient and control samples. The samples are used to train classifiers to accurately classify the samples on a per miRNA basis. Multiple high scoring miRNAs are used to build a final classifier to improve separation.
Computational Prediction of Functional MicroRNA–mRNA Interactions
Saçar Demirci,, Müşerref D. ; Yousef, Malik ; Allmer, Jens - \ 2019
In: Computational Biology of Non-Coding RNA New York : Springer (Methods in Molecular Biology ) - ISBN 9781493989812 - p. 175 - 196.
Proteins have a strong influence on the phenotype and their aberrant expression leads to diseases. MicroRNAs (miRNAs) are short RNA sequences which posttranscriptionally regulate protein expression. This regulation is driven by miRNAs acting as recognition sequences for their target mRNAs within a larger regulatory machinery. A miRNA can have many target mRNAs and an mRNA can be targeted by many miRNAs which makes it difficult to experimentally discover all miRNA–mRNA interactions. Therefore, computational methods have been developed for miRNA detection and miRNA target prediction. An abundance of available computational tools makes selection difficult. Additionally, interactions are not currently the focus of investigation although they more accurately define the regulation than pre-miRNA detection or target prediction could perform alone. We define an interaction including the miRNA source and the mRNA target. We present computational methods allowing the investigation of these interactions as well as how they can be used to extend regulatory pathways. Finally, we present a list of points that should be taken into account when investigating miRNA–mRNA interactions. In the future, this may lead to better understanding of functional interactions which may pave the way for disease marker discovery and design of miRNA-based drugs.
Species categorization via MicroRNAs based on 3’UTR target sites using sequence features
Yousef, Malik ; Levy, Dalit ; Allmer, Jens - \ 2018
In: Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies. - SciTePress - ISBN 9789897582806 - p. 112 - 118.
Categorization - Machine Learning - MicroRNA - MicroRNA Target - Sequence Features

Proteins define phenotypes and their dysregulation leads to diseases. Post-translational regulation of protein abundance can be achieved by microRNAs (miRNAs). Therefore studying this method of gene regulation is of high importance. MicroRNAs interact with their target messenger RNA via hybridization within a specialized molecular framework. Many miRNAs and their targets have been identified and they are listed in various databases like miRTarBase. The experimental identification of functional miRNA-mRNA pairs is difficult and, therefore, they are detected computationally which is complicated due to missing negative data. Machine learning has been used for miRNA and target detection and many features have been described for miRNAs and miRNA:mRNA target duplexes generally on a per species basis. However, many claims of cross-kingdom regulation via miRNAs have been made and, therefore, we were interested whether it is possible to differentiate among species based on the target sequence in the mRNA alone. Thus, we investigated whether miRNA targets sites within the 3’UTR can be differentiated between species based on k-mer features only. Target information of one species was used as positive examples and the others as negative ones to establish machine learning models. It was observed that few features were sufficient for successful categorization of mircoRNA targets to species. For example mouse versus Caenorhabditis elegans reached up to 97% average accuracy over 100 fold cross validation. The simplicity of the approach, based on just k-mers, is promising for automatic categorization systems. In the future, this approach will help scrutinize alleged cross-kingdom regulation via miRNAs in respect to miRNA from one species targeting mRNAs in another.

Categorization of species based on their microRNAs employing sequence motifs, information-theoretic sequence feature extraction, and k-mers
Yousef, Malik ; Nigatu, Dawit ; Levy, Dalit ; Allmer, Jens ; Henkel, Werner - \ 2017
Eurasip Journal on Advances in Signal Processing 2017 (2017). - ISSN 1687-6172 - 10 p.
Differentiate miRNAs among species - Information theory - k-mer - Machine learning - MicroRNA - miRNA categorization - Pre-microRNA - Sequence motifs

Background: Diseases like cancer can manifest themselves through changes in protein abundance, and microRNAs (miRNAs) play a key role in the modulation of protein quantity. MicroRNAs are used throughout all kingdoms and have been shown to be exploited by viruses to modulate their host environment. Since the experimental detection of miRNAs is difficult, computational methods have been developed. Many such tools employ machine learning for pre-miRNA detection, and many features for miRNA parameterization have been proposed. To train machine learning models, negative data is of importance yet hard to come by; therefore, we recently started to employ pre-miRNAs from one species as positive data versus another species’ pre-miRNAs as negative examples based on sequence motifs and k-mers. Here, we introduce the additional usage of information-theoretic (IT) features. Results: Pre-miRNAs from one species were used as positive and another species’ pre-miRNAs as negative training data for machine learning. The categorization capability of IT and k-mer features was investigated. Both feature sets and their combinations yielded a very high accuracy, which is as good as the previously suggested sequence motif and k-mer based method. However, for obtaining a high performance, a sufficiently large phylogenetic distance between the species and sufficiently high number of pre-miRNAs in the training set is required. To examine the contribution of the IT and k-mer features, an information gain-based feature ranking was performed. Although the top 3 are IT features, 80% of the top 100 features are k-mers. The comparison of all three individual approaches (motifs, IT, and k-mers) shows that the distinction of species based on their pre-miRNAs k-mers are sufficient. Conclusions: IT sequence feature extraction enables the distinction among species and is less computationally expensive than motif calculations. However, since IT features need larger amounts of data to have enough statistics for producing highly accurate results, future categorization into species can be effectively done using k-mers only. The biological reasoning for this is the existence of a codon bias between species which can, at least, be observed in exonic miRNAs. Future work in this direction will be the ab initio detection of pre-miRNA. In addition, prediction of pre-miRNA from RNA-seq can be done.

Burden of diarrhea in the eastern mediterranean region, 1990-2013 : Findings from the global burden of disease study 2013
Khalil, Ibrahim ; Colombara, Danny V. ; Forouzanfar, Mohammad Hossein ; Troeger, Christopher ; Daoud, Farah ; Moradi-Lakeh, Maziar ; Bcheraoui, Charbel El; Rao, Puja C. ; Afshin, Ashkan ; Charara, Raghid ; Abate, Kalkidan Hassen ; Abd El Razek, Mohammed Magdy ; Abd-Allah, Foad ; Abu-Elyazeed, Remon ; Kiadaliri, Aliasghar Ahmad ; Akanda, Ali Shafqat ; Akseer, Nadia ; Alam, Khurshid ; Alasfoor, Deena ; Ali, Raghib ; AlMazroa, Mohammad A. ; Alomari, Mahmoud A. ; Salem Al-Raddadi, Rajaa Mohammad ; Alsharif, Ubai ; Alsowaidi, Shirina ; Altirkawi, Khalid A. ; Alvis-Guzman, Nelson ; Ammar, Walid ; Antonio, Carl Abelardo T. ; Asayesh, Hamid ; Asghar, Rana Jawad ; Atique, Suleman ; Awasthi, Ashish ; Bacha, Umar ; Badawi, Alaa ; Barac, Aleksandra ; Bedi, Neeraj ; Bekele, Tolesa ; Bensenor, Isabela M. ; Betsu, Balem Demtsu ; Bhutta, Zulfiqar ; Abdulhak, Aref A. Bin; Butt, Zahid A. ; Danawi, Hadi ; Dubey, Manisha ; Endries, Aman Yesuf ; Faghmous, Imad M.D.A. ; Farid, Talha ; Farvid, Maryam S. ; Farzadfar, Farshad ; Fereshtehnejad, Seyed Mohammad ; Fischer, Florian ; Anderson Fitchett, Joseph Robert ; Gibney, Katherine B. ; Mohamed Ginawi, Ibrahim Abdelmageem ; Gishu, Melkamu Dedefo ; Gugnani, Harish Chander ; Gupta, Rahul ; Hailu, Gessessew Bugssa ; Hamadeh, Randah Ribhi ; Hamidi, Samer ; Harb, Hilda L. ; Hedayati, Mohammad T. ; Hsairi, Mohamed ; Husseini, Abdullatif ; Jahanmehr, Nader ; Javanbakht, Mehdi ; Beyene, Tariku ; Jonas, Jost B. ; Kasaeian, Amir ; Khader, Yousef Saleh ; Khan, Abdur Rahman ; Khan, Ejaz Ahmad ; Khan, Gulfaraz ; Khoja, Tawfik Ahmed Muthafer ; Kinfu, Yohannes ; Kissoon, Niranjan ; Koyanagi, Ai ; Lal, Aparna ; Abdul Latif, Asma Abdul ; Lunevicius, Raimundas ; Abd El Razek, Hassan Magdy ; Majeed, Azeem ; Malekzadeh, Reza ; Mehari, Alem ; Mekonnen, Alemayehu B. ; Melaku, Yohannes Adama ; Memish, Ziad A. ; Mendoza, Walter ; Misganaw, Awoke ; Ibrahim Mohamed, Layla Abdalla ; Nachega, Jean B. ; Nguyen, Quyen Le ; Nisar, Muhammad Imran ; Peprah, Emmanuel Kwame ; Platts-Mills, James A. ; Pourmalek, Farshad ; Qorbani, Mostafa ; Rafay, Anwar ; Rahimi-Movaghar, Vafa ; Ur Rahman, Sajjad ; Rai, Rajesh Kumar ; Rana, Saleem M. ; Ranabhat, Chhabi L. ; Rao, Sowmya R. ; Refaat, Amany H. ; Riddle, Mark ; Roshandel, Gholamreza ; Ruhago, George Mugambage ; Saleh, Muhammad Muhammad ; Sanabria, Juan R. ; Sawhney, Monika ; Sepanlou, Sadaf G. ; Setegn, Tesfaye ; Sliwa, Karen ; Sreeramareddy, Chandrashekhar T. ; Sykes, Bryan L. ; Tavakkoli, Mohammad ; Tedla, Bemnet Amare ; Terkawi, Abdullah S. ; Ukwaja, Kingsley ; Uthman, Olalekan A. ; Westerman, Ronny ; Wubshet, Mamo ; Yenesew, Muluken A. ; Yonemoto, Naohiro ; Younis, Mustafa Z. ; Zaidi, Zoubida ; Sayed Zaki, Maysaa El; Rabeeah, Abdullah A. Al; Wang, Haidong ; Naghavi, Mohsen ; Vos, Theo ; Lopez, Alan D. ; Murray, Christopher J.L. ; Mokdad, Ali H. - \ 2016
American Journal of Tropical Medicine and Hygiene 95 (2016)6. - ISSN 0002-9637 - p. 1319 - 1329.

Diarrheal diseases (DD) are leading causes of disease burden, death, and disability, especially in children in low-income settings. DD can also impact a child's potential livelihood through stunted physical growth, cognitive impairment, and other sequelae. As part of the Global Burden of Disease Study, we estimated DD burden, and the burden attributable to specific risk factors and particular etiologies, in the Eastern Mediterranean Region (EMR) between 1990 and 2013. For both sexes and all ages, we calculated disability-adjusted life years (DALYs), which are the sum of years of life lost and years lived with disability. We estimate that over 125,000 deaths (3.6% of total deaths) were due to DD in the EMR in 2013, with a greater burden of DD in low-and middle-income countries. Diarrhea deaths per 100,000 children under 5 years of age ranged from one (95% uncertainty interval [UI] = 0-1) in Bahrain and Oman to 471 (95% UI = 245-763) in Somalia. The pattern for diarrhea DALYs among those under 5 years of age closely followed that for diarrheal deaths. DALYs per 100,000 ranged from 739 (95% UI = 520-989) in Syria to 40,869 (95% UI = 21,540-65,823) in Somalia. Our results highlighted a highly inequitable burden of DD in EMR, mainly driven by the lack of access to proper resources such as water and sanitation. Our findings will guide preventive and treatment interventions which are based on evidence and which follow the ultimate goal of reducing the DD burden.

Verdronken land
Jongerden, J. ; Yousef, A. - \ 2000
Soera : tijdschrift over het Midden-Oosten 8 (2000)1. - ISSN 0929-1679 - p. 37 - 39.
A nematode survey of vegetable crops and some orchards in the ghor of Jordan.
Yousef, D.M. ; Jacob, J.J. 's - \ 1994
Nematologia Mediterranea 22 (1994). - ISSN 0391-9749 - p. 11 - 15.
Pollutant removal and eutrophication in urban runoff detention ponds.
Toet, C. ; Hvitved-Jacobsen, T. ; Yousef, Y.A. - \ 1989
In: Proc. 2nd Wageningen Conf. Urban storm water quality and ecological effects upon receiving waters. CHO/TNO Committee Hydrological Research, The Netherlands (1989)
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