Changiz Eslahchi
Shahid Beheshti University, Computer Science, Faculty Member
- Changiz Eslahchi is a professor in the department of computer sciences, school of mathematics, Shahid Beheshti Univer... moreChangiz Eslahchi is a professor in the department of computer sciences, school of mathematics, Shahid Beheshti University and a senior researcher at school of biological sciences, Institute for Research in Fundamental Sciences, Tehran, Iran. He is vice dean of the school of mathematics of Shahid Beheshti university now. He currently works mostly on algorithms in bioinformatics and their application to biomedicine. He has also done, especially in the earlier part of his career, some research in graph theory. Changiz has written about 70 research papers. Changiz was a member of the team of introducing bioinformatics in Iran. Changiz and his colleague’s effort led to create the first PhD program in bioinformatics in Iran. He received his MA in mathematics from Shiraz University and his PhD in 1998 from Sharif University of Technology Tehran, Iran.edit
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In this paper we present TripNet, a method for constructing phylogenetic networks from triplets. We will present the motivations behind our approach and its theoretical and empirical justification. To demonstrate the accuracy and... more
In this paper we present TripNet, a method for constructing phylogenetic networks from triplets. We will present the motivations behind our approach and its theoretical and empirical justification. To demonstrate the accuracy and efficiency of TripNet, we performed two simulations and also applied the method to some published data. Surprisingly, the results show that we can construct an accurate phylogenetic network using a small amount of information.
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Let G be a simple graph. The Hosoya polynomial of G is ( , ) , ( , ) = { , } ( ) xd u v H G x u v V G where d(u,v) denotes the distance between vertices u and v . The dendrimer nanostar is a part of a new group of macromolecules. In... more
Let G be a simple graph. The Hosoya polynomial of G is ( , ) , ( , ) = { , } ( ) xd u v H G x u v V G where d(u,v) denotes the distance between vertices u and v . The dendrimer nanostar is a part of a new group of macromolecules. In this paper we compute the Hosoya polynomial for an infinite family of dendrimer nanostar. As a consequence we obtain the Wiener index and the hyper-Wiener index of this dendrimer.
Research Interests: Mathematics, Combinatorics, Graph, Macromolecule, Iranian, and 3 moreDendrimer, Wiener Index, and Polynomial
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Localization of messenger RNAs (mRNA) as a widely observed phenomenon is considered as an efficient way to target proteins to a specific region of a cell and is also known as a strategy for gene regulation. The importance of correct... more
Localization of messenger RNAs (mRNA) as a widely observed phenomenon is considered as an efficient way to target proteins to a specific region of a cell and is also known as a strategy for gene regulation. The importance of correct intracellular RNA placement in the development of embryonic and neural dendrites has long been demonstrated in former studies. Improper localization of RNA in the cell, which has been shown to occur due to a variety of reasons, including mutations in trans-regulatory elements, is also associated with the occurrence of some neuromuscular diseases as well as cancer. We propose NN-RNALoc, a neural network-based model to predict the cellular location of mRNAs. The features extracted from mRNA sequences along with the information gathered from their proteins are fed to this prediction model. We introduce a novel distance-based sub-sequence profile for representation of RNA sequences which is more memory and time efficient and comparying to the k-mer frequenci...
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Cancer research aims to identify genes that cause or control disease progression. Although a wide range of gene sets have been published, they are usually in poor agreement with one another. Furthermore, recent findings from a... more
Cancer research aims to identify genes that cause or control disease progression. Although a wide range of gene sets have been published, they are usually in poor agreement with one another. Furthermore, recent findings from a gene-expression cohort of different cancer types, known as positive random bias, showed that sets of genes chosen randomly are significantly associated with survival time much higher than expected. In this study, we propose a method based on Brouwer’s fixed-point theorem that employs significantly survival-associated random gene sets and reveals a small fixed-point gene set for cancers with a positive random bias property. These sets significantly correspond to cancer-related pathways with biological relevance for the progression and metastasis of the cancer types they represent. Our findings show that our proposed significant gene sets are biologically related to each cancer type available in the cancer genome atlas with the positive random bias property, and...
Background: The relationship between Diabetes Mellitus (DM) and Alzheimer's Disease (AD) is so strong that scientists called it "brain diabetes". According to several studies, the critical factor in this relationship is... more
Background: The relationship between Diabetes Mellitus (DM) and Alzheimer's Disease (AD) is so strong that scientists called it "brain diabetes". According to several studies, the critical factor in this relationship is brain insulin resistance. Due to the rapid spread of both diseases throughout the world, overcoming this cross-talk has a significant impact on societies. Long non-coding RNAs (lnc RNAs), on the other hand, have a substantial impact on complex diseases due to their ability to influence gene expression via a variety of mechanisms. As a result, regulating the expression of lncRNAs in chronic diseases enables the development of novel therapeutic strategies. However, developing a new drug requires considerable time and money. Recently repurposing existing drugs has gained popularity due to the use of low-risk compounds, which may result in cost and time savings.Results: We identified drug repurposing candidates that could control the expression of common ln...
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Methods for detecting protein complexes from protein-protein interaction networks are of the most critical computational approaches. Numerous methods have been proposed in this area. Therefore, it is necessary to evaluate them. Various... more
Methods for detecting protein complexes from protein-protein interaction networks are of the most critical computational approaches. Numerous methods have been proposed in this area. Therefore, it is necessary to evaluate them. Various metrics have been proposed in order to compare these methods. Nevertheless, it is essential to define new metrics that evaluate methods both qualitatively and quantitatively. In addition, there is no tool for the comprehensive comparison of such methods. In this paper, a new criterion is introduced that can fully evaluate protein complex detection algorithms. We introduce CDAP (Complex Detection Analyzer Package); an online package for comparing protein complex detection methods. CDAP can quickly rank the performance of methods based on previously defined as well as newly introduced criteria in various settings (4 PPI datasets and 3 gold standards). It has the capability of integrating various methods and apply several filterings on the results. CDAP ...
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An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Though proposing algorithmic approaches for protein domain decomposition has been of high interest, the inherent ambiguity to the problem makes it still an active area of research. Besides, accurate automated methods are in high demand as... more
Though proposing algorithmic approaches for protein domain decomposition has been of high interest, the inherent ambiguity to the problem makes it still an active area of research. Besides, accurate automated methods are in high demand as the number of solved structures for complex proteins is on the rise. While majority of the previous efforts for decomposition of 3D structures are centered on the developing clustering algorithms, employing enhanced measures of proximity between the amino acids has remained rather uncharted. If there exists a kernel function that in its reproducing kernel Hilbert space, structural domains of proteins become well separated, then protein structures can be parsed into domains without the need to use a complex clustering algorithm. Inspired by this idea, we developed a protein domain decomposition method based on diffusion kernels on protein graphs. We examined all combinations of four graph node kernels and two clustering algorithms to investigate the...
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BackgroundRecent research has investigated the connection between Diabetes Mellitus (DM) and Alzheimer’s Disease (AD). Insulin resistance plays a crucial role in this interaction. Studies have focused on dysregulated proteins to disrupt... more
BackgroundRecent research has investigated the connection between Diabetes Mellitus (DM) and Alzheimer’s Disease (AD). Insulin resistance plays a crucial role in this interaction. Studies have focused on dysregulated proteins to disrupt this connection. Non-coding RNAs (ncRNAs), on the other hand, play an important role in the development of many diseases. They encode the majority of the human genome and regulate gene expression through a variety of mechanisms. Consequently, identifying significant ncRNAs and utilizing them as biomarkers could facilitate the early detection of this cross-talk. On the other hand, computational-based methods may help to understand the possible relationships between different molecules and conduct future wet laboratory experiments.Materials and methodsIn this study, we retrieved Genome-Wide Association Study (GWAS, 2008) results from the United Kingdom Biobank database using the keywords “Alzheimer’s” and “Diabetes Mellitus.” After excluding low confid...
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Additional file 1. Different hyperparameters values for 964 side effects of each model, and the results of 10 best and worst performance of polypharmacy side effects in NNPS and Decagon on AUROC and AUPRC. Bold numbers show the best... more
Additional file 1. Different hyperparameters values for 964 side effects of each model, and the results of 10 best and worst performance of polypharmacy side effects in NNPS and Decagon on AUROC and AUPRC. Bold numbers show the best performance for each criteria.
Gene regulatory networks explain how cells control the expression of genes, which, together with some additional regulation downstream, determines the production of proteins essential for cellular function. Bayesian networks (BNs) are... more
Gene regulatory networks explain how cells control the expression of genes, which, together with some additional regulation downstream, determines the production of proteins essential for cellular function. Bayesian networks (BNs) are practical tools which have been successfully implemented in learning gene networks based on microarray gene expression data. Bayesian networks are graphical representation for probabilistic relationships among a set of random variables. PC algorithm is a structure learning algorithm based on conditional independence tests. The drawback of PC algorithm is that high-order conditional independence (CI) tests need large sample sizes. The number of records in microarray dataset is rarely enough to perform reliable high-order CI tests. In this paper, we extend the methodology for reduction of the order of the CI tests. In order to improve the PC algorithm, we introduce a heuristic algorithm, LSPC, for learning the structure of the BN. The results indicate th...
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Comparison between protein contact maps is an essential component of proteomic research. Biological role of protein is derived from its third structure, any promotion in predicting protein structure shows its impact in drug design and the... more
Comparison between protein contact maps is an essential component of proteomic research. Biological role of protein is derived from its third structure, any promotion in predicting protein structure shows its impact in drug design and the other biology's ...
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A proper edge coloring of a simple graph G from some lists assigned to the edges of G is of interest. A. Hilton and P. Johnson (1990) considered a necessary condition for the list coloring of a graph and called it Hall's condition.... more
A proper edge coloring of a simple graph G from some lists assigned to the edges of G is of interest. A. Hilton and P. Johnson (1990) considered a necessary condition for the list coloring of a graph and called it Hall's condition. They introduced the Hall index of a graph G, h'(G), as the smallest positive integer m such that there exists a list coloring whenever the lists are of length at least m and Hall's condition is satisfied. They characterized all graphs G with h' (G) = 1. In this paper we characterize the graphs with Hall index 2.
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<p>The PC Algorithm based on CMI test (PCA-CMI) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092600#pone.0092600-Zhang1" target="_blank">[5]</a>.</p
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Mathematics Interdisciplinary Research (MIR) publishes quality original research papers and survey articles in Interdisciplinary Mathematics that are of the highest possible quality. The editorial board of this journal comprises experts... more
Mathematics Interdisciplinary Research (MIR) publishes quality original research papers and survey articles in Interdisciplinary Mathematics that are of the highest possible quality. The editorial board of this journal comprises experts from around the world. The papers in the relationship between two different scientific disciplines are of high interest for MIR. The research papers and review articles are selected through a normal refereeing process by a member of editorial board. A paper acceptable for publication must contain non-trivial mathematics with clear applications to other parts of science and engineering. MIR motivates authors to publish significant research papers, which are of broad interests in Applications of Mathematics in Science. Two issues in one volume are published every year. Aims and Scope: MIR contains research articles in the form of expository papers, original scientific article, short communications on important mathematical problems of basic sciences an...
Abstract. In this paper, all graphs and hypergraphs are finite. For any ordered hypergraph H, the associated graph GH of H is defined. Some basic graph-theoretic properties of H and GH are compared and studied in general and specially via... more
Abstract. In this paper, all graphs and hypergraphs are finite. For any ordered hypergraph H, the associated graph GH of H is defined. Some basic graph-theoretic properties of H and GH are compared and studied in general and specially via the largest negative real root of the clique polynomial of GH. It is also shown that any hypergraph H contains an ordered subhypergraph whose associated graph reflects some graph-theoretic properties of H. Finally, we define the depth of a hypergraph H and introduce a constructive algorithm for coloring of H. 1.
The ongoing pandemic of a novel coronavirus (SARS-CoV-2) leads to international concern; thus, emergency interventions need to be taken. Due to the time-consuming experimental methods for proposing useful treatments, computational... more
The ongoing pandemic of a novel coronavirus (SARS-CoV-2) leads to international concern; thus, emergency interventions need to be taken. Due to the time-consuming experimental methods for proposing useful treatments, computational approaches facilitate investigating thousands of alternatives simultaneously and narrow down the cases for experimental validation. Herein, we conducted four independent analyses for RNA interference (RNAi)-based therapy with computational and bioinformatic methods. The aim is to target the evolutionarily conserved regions in the SARS-CoV-2 genome in order to down-regulate or silence its RNA. miRNAs are denoted to play an important role in the resistance of some species to viral infections. A comprehensive analysis of the miRNAs available in the body of humans, as well as the miRNAs in bats and many other species, were done to find efficient candidates with low side effects in the human body. Moreover, the evolutionarily conserved regions in the SARS-CoV-2...
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In recent years, due to the difficulty and inefficiency of experimental methods, numerous computational methods have been introduced for inferring the structure of Gene Regulatory Networks (GRNs). The Path Consistency (PC) algorithm is... more
In recent years, due to the difficulty and inefficiency of experimental methods, numerous computational methods have been introduced for inferring the structure of Gene Regulatory Networks (GRNs). The Path Consistency (PC) algorithm is one of the popular methods to infer the structure of GRNs. However, this group of methods still has limitations and there is a potential for improvements in this field. For example, the PC-based algorithms are still sensitive to the ordering of nodes i.e. different node orders results in different network structures. The second is that the networks inferred by these methods are highly dependent on the threshold used for independence testing. Also, it is still a challenge to select the set of conditional genes in an optimal way, which affects the performance and computation complexity of the PC-based algorithm. We introduce a novel algorithm, namely Order Independent PC-based algorithm using Quantile value (OIPCQ), which improves the accuracy of the le...
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Background Distant metastasis of Gastric Cancer (GC) causes more than 700 000 deaths worldwide. Cancer Stem Cells (CSCs) are a subpopulation of cancer cells responsible for aggressiveness and chemoresistance in clinical settings.... more
Background Distant metastasis of Gastric Cancer (GC) causes more than 700 000 deaths worldwide. Cancer Stem Cells (CSCs) are a subpopulation of cancer cells responsible for aggressiveness and chemoresistance in clinical settings. MicroRNAs (miRNAs) emerge as important players in regulating self-renewal and metastasis in CSCs. Understanding the role of miRNAs in CSCs offer a potential diagnostic tool for GC patients. This study is aimed to identify miRNAs that target both stemness and metastasis in gastric cancer stem cells (GCSCs) and differentially expressed in metastatic GC patients as diagnostic biomarkers for GC metastasis. Methods We investigate the gene expression profile of patients using the GEO database and Rstudio software. To obtain the regulatory networks and miRNAs, the STRING and miRwalk database used. The gastric cancer tissues were obtained from Iranian National Tumor Bank (INTB) to validate the results. Results Our results indicated three important regulatory cores ...
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Background Polypharmacy is a type of treatment that involves the concurrent use of multiple medications. Drugs may interact when they are used simultaneously. So, understanding and mitigating polypharmacy side effects are critical for... more
Background Polypharmacy is a type of treatment that involves the concurrent use of multiple medications. Drugs may interact when they are used simultaneously. So, understanding and mitigating polypharmacy side effects are critical for patient safety and health. Since the known polypharmacy side effects are rare and they are not detected in clinical trials, computational methods are developed to model polypharmacy side effects. Results We propose a neural network-based method for polypharmacy side effects prediction (NNPS) by using novel feature vectors based on mono side effects, and drug–protein interaction information. The proposed method is fast and efficient which allows the investigation of large numbers of polypharmacy side effects. Our novelty is defining new feature vectors for drugs and combining them with a neural network architecture to apply for the context of polypharmacy side effects prediction. We compare NNPS on a benchmark dataset to predict 964 polypharmacy side ef...
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The hydrogen/deuterium exchange (HDX) is a reliable method to survey the dynamic behavior of proteins and epitope mapping. Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) is a quantifying tool... more
The hydrogen/deuterium exchange (HDX) is a reliable method to survey the dynamic behavior of proteins and epitope mapping. Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) is a quantifying tool to assay for HDX in the protein of interest. We combined HDX-MALDI-TOF MS and molecular docking/MD simulation to identify accessible amino acids and analyze their contribution in the structural changes of profilin1 (PFN1). The molecular docking/MD simulations are computational tools for enabling the analysis of the type of amino acids that may be involved via HDX identified under the lowest binding energy condition. Glycine to Valine amino acid (G117V) substitution mutation is linked to amyotrophic lateral sclerosis (ALS). This mutation is found to be in the actin-binding site of PFN1 and prevents the dimerization/polymerization of actin and invokes a pathologic toxicity that leads to ALS. In this study, we sought to understand the PFN1 protein dynam...
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A tale of two symmetrical tails: Structural and functional
Removal or suppression of key proteins in an essential pathway of a pathogen is expected to disrupt the pathway and prohibit the pathogen from performing a vital function. Thus disconnecting multiple essential pathways should disrupt the... more
Removal or suppression of key proteins in an essential pathway of a pathogen is expected to disrupt the pathway and prohibit the pathogen from performing a vital function. Thus disconnecting multiple essential pathways should disrupt the survival of a pathogen even when it has multiple pathways to drug resistance. We consider a scenario where the drug-resistance pathways are unknown. To disrupt these pathways, we consider a cut set S of G, where G is a connected simple graph representing the protein interaction network of the pathogen, so that G-S splits to two partitions such that the endpoints of each pathway are in different partitions. If the difference between the sizes of the two partitions is high, the probability of existence of a functioning pathway in one partition is increased. Thus, we need to partition the graph into two balanced partitions. We approximate the balanced bipartitioning problem with spectral bipartitioning since finding (2,1)-separator is NP-complete. We t...
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Abstract—One of the most important issues in this challenge is to find regulatory elements, especially the binding sites in DNA sequence for transcription factors. The binding sites for co-expressed genes are short similar subsequences... more
Abstract—One of the most important issues in this challenge is to find regulatory elements, especially the binding sites in DNA sequence for transcription factors. The binding sites for co-expressed genes are short similar subsequences that are called motifs. The performance of any motif finding algorithm can be measured by how well it is able to identify true binding sites in a data set. Our algorithm can detect new binding sites on a data set and it is an enumerative algorithm which can be considered as a complementary motif finding algorithm. The LIBRA algorithm is designed for any kind of input sequence organism. Availability: LIBRA is downloadable from
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Research Interests: Algorithms, Computational Biology, Gene Prediction, Biological Sciences, Humans, and 15 moreMarkov chains, Mathematical Sciences, Animals, BMC Bioinformatics, Gene Structure, Information Content, Genomic DNA, Genome sequence, Likelihood Functions, Nucleic Acid Conformation, Computational Method, Nucleotides, Markov model, BMC, and Higher order
Protein complexes are a cornerstone of many biological processes and, together, they form various types of molecular machinery that perform a vast array of biological functions. Di®erent complexes perform di®erent functions and, the same... more
Protein complexes are a cornerstone of many biological processes and, together, they form various types of molecular machinery that perform a vast array of biological functions. Di®erent complexes perform di®erent functions and, the same complex can perform very di®erent func-tions that depend on a variety of factors. Thus disruption of protein complexes can be lethal to an organism. It is interesting to identify a minimal set of proteins whose removal would lead to a massive disruption of protein complexes and, to understand the biological properties of these proteins. A method is presented for identifying a minimum number of proteins from a given set of complexes so that a maximum number of these complexes are disrupted when these proteins are removed. The method is based on spectral bipartitioning. This method is applied to yeast protein complexes. The identi¯ed proteins participate in a large number of biological processes and functional modules. A large proportion of them are e...
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eslahchi~karun.ipm.ac.ir
Single Nucleotide Polymorphisms (SNPs) are the most usual form of polymorphism in human genome. Analyses of genetic variations have revealed that individual genomes share common SNP-haplotypes. The particular pattern of these common... more
Single Nucleotide Polymorphisms (SNPs) are the most usual form of polymorphism in human genome. Analyses of genetic variations have revealed that individual genomes share common SNP-haplotypes. The particular pattern of these common variations forms a block-like structure on human genome. In this work, we develop a new method based on the Perfect Phylogeny Model to identify haplotype blocks using samples of individual genomes. We introduce a rigorous definition of the quality of the partitioning of haplotypes into blocks and devise a greedy algorithm for finding the proper partitioning in case of perfect and semi-perfect phylogeny. It is shown that the minimum number of tagSNPs in a haplotype block of Perfect Phylogeny can be obtained by a polynomial time algorithm. We compare the performance of our algorithm on haplotype data of human chromosome 21 with other previously developed methods through simulations. The results demonstrate that our algorithm outperforms the conventional im...
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Assignment of structural domains in complex protein structures is an important task in bioinformatics researches. As the number of known protein structures grows rapidly, the need for automatic methods for determining protein domains... more
Assignment of structural domains in complex protein structures is an important task in bioinformatics researches. As the number of known protein structures grows rapidly, the need for automatic methods for determining protein domains based on the proteins tree-dimensional structure becomes more desirable. In this paper, we introduce a new domain decomposition algorithm which is based on the dominating set of the graph representation of a protein. To evaluate our method, we compare our results with the other computational methods on a commonly used benchmark of 55 proteins. It is shown that the performance of our algorithm is better than the other automatic methods.
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The automatic assignment of the protein secondary structure from three dimensional coordinates is an essential step in the characterization of protein structure. Although the recognition of secondary structure elements as alpha helices... more
The automatic assignment of the protein secondary structure from three dimensional coordinates is an essential step in the characterization of protein structure. Although the recognition of secondary structure elements as alpha helices and beta sheets seem ...
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The concept of circular chromatic number of graphs was introduced by Vince(1988). In this paper we define circular chromatic number of uniform hypergraphs and study their basic properties. We study the relationship between circular... more
The concept of circular chromatic number of graphs was introduced by Vince(1988). In this paper we define circular chromatic number of uniform hypergraphs and study their basic properties. We study the relationship between circular chromatic number with chromatic number and fractional chromatic number of uniform hypergraphs.
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In this paper we define the concept of clique number of uniform hypergraph and study its relationship with circular chromatic number and clique number. For every positive integer k,p and q, 2q ≤ p we construct a k-uniform hypergraph H... more
In this paper we define the concept of clique number of uniform hypergraph and study its relationship with circular chromatic number and clique number. For every positive integer k,p and q, 2q ≤ p we construct a k-uniform hypergraph H with small clique number whose circular chromatic number equals p q . We define the concept and study the properties of c-perfect k-uniform hypergraphs .
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In thispaper a conjecture of A. Hilton and P. Johnson on list coloring of graphs is disproved. By modifying our counterexample, we also answer some other questions concerning Hall numbers.
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This study aimed to investigate four of the eight PFN-1 mutations that are located near the actin-binding domain and determine the structural changes due to each mutant and unravel how these mutations alter protein structural behavior.... more
This study aimed to investigate four of the eight PFN-1 mutations that are located near the actin-binding domain and determine the structural changes due to each mutant and unravel how these mutations alter protein structural behavior. Swapaa’s command in UCSF chimera for generating mutations, FTMAP were employed and the data was analyzed by RMSD, RMSF graphs, Rg, hydrogen bonding analysis, and RRdisMaps utilizing Autodock4 and GROMACS. The functional changes and virtual screening, structural dynamics, and chemical bonding behavior changes, molecular docking simulation with two current FDA-approved drugs for ALS were investigated. The highest reduction and increase in Rg were found to exist in the G117V and M113T mutants, respectively. The RMSF data consistently shows changes nearby to this site. The in silico data described indicate that each of the mutations is capable of altering the structure of PFN-1 in vivo. The potential effect of riluzole and edaravone two FDA approved drugs...
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We present TripNet, a method for constructing phylogenetic networks from triplets. We will present the motivations behind our approach and its theoretical and empirical justification. To demonstrate the accuracy and efficiency of TripNet,... more
We present TripNet, a method for constructing phylogenetic networks from triplets. We will present the motivations behind our approach and its theoretical and empirical justification. To demonstrate the accuracy and efficiency of TripNet, we performed two simulations and also applied the method to five published data sets: Kreitman's data, a set of triplets from real yeast data obtained from the Fungal Biodiversity Center in Utrecht, a collection of 110 highly recombinant Salmonella multi-locus sequence typing sequences, and nrDNA ITS and cpDNA JSA sequence data of New Zealand alpine buttercups of Ranunculus sect. Pseudadonis. Finally, we compare our results with those already obtained by other authors using alternative methods. TripNet, data sets, and supplementary files are freely available for download at (www.bioinf.cs.ipm.ir/softwares/tripnet).
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Protein structure comparison is an important problem in bioinformatics and has many applications in the study of structural and functional genomics. During the last decades, various heuristic methods have been developed to solve the... more
Protein structure comparison is an important problem in bioinformatics and has many applications in the study of structural and functional genomics. During the last decades, various heuristic methods have been developed to solve the protein structure comparison problem. Most of the protein structure comparison methods give the alignment based on the minimum RMSD (root mean square deviation) and ignore many significant local alignments that may be important for evolutional or functional studies. We have developed a new algorithm to find aligned residues in two proteins with desired RMSD value. The parameterized distance and rotation in this program enable us to search for strongly or weakly similar aligned fragments in two proteins. © 2009 Published by Elsevier Ltd.
The problem of constructing an optimal rooted phylogenetic network from a set of rooted triplets is NP-hard. In this paper, we present a novel method called NCH, which tries to construct a rooted phylogenetic network with the... more
The problem of constructing an optimal rooted phylogenetic network from a set of rooted triplets is NP-hard. In this paper, we present a novel method called NCH, which tries to construct a rooted phylogenetic network with the minimum numberof reticulation nodes from an arbitrary set of rooted triplets based on the concept of the height function of a tree and a network. We report the performance of this method on simulated data. Keywords— Rooted phylogenetic network, Triplet, Density, Consistency, Height function, Reticulation node
Research Interests: Density and Consistency
Background: Polypharmacy is a type of treatment that involves the concurrent use of multiple medications. Drugs may interact when they are used simultaneously. So, understanding and mitigating polypharmacy side effects are critical for... more
Background: Polypharmacy is a type of treatment that involves the concurrent use of multiple medications. Drugs may interact when they are used simultaneously. So, understanding and mitigating polypharmacy side effects are critical for patient safety and health. Since the known polypharmacy side effects are rare and they are not detected in clinical trials, computational methods are developed to model polypharmacy side effects. Results: We propose a neural network-based method for polypharmacy side effects prediction (NNPS) by using novel feature vectors based on mono side effects, and drug-protein interaction information. The proposed method is fast and efficient which allows the investigation of large numbers of polypharmacy side effects. Our novelty is defining new feature vectors for drugs and combining them with a neural network architecture to apply for the context of polypharmacy side effects prediction. We compare NNPS on a benchmark dataset to predict 964 polypharmacy side ...
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Motivation One of the most difficult challenges in precision medicine is determining the best treatment strategy for each patient based on personal information. Since drug response prediction in vitro is extremely expensive,... more
Motivation One of the most difficult challenges in precision medicine is determining the best treatment strategy for each patient based on personal information. Since drug response prediction in vitro is extremely expensive, time-consuming and virtually impossible, and because there are so many cell lines and drug data, computational methods are needed. Results MinDrug is a method for predicting anti-cancer drug response which try to identify the best subset of drugs that are the most similar to other drugs. MinDrug predicts the anti-cancer drug response on a new cell line using information from drugs in this subset and their connections to other drugs. MinDrug employs a heuristic star algorithm to identify an optimal subset of drugs and a regression technique known as Elastic-Net approaches to predict anti-cancer drug response in a new cell line. To test MinDrug, we use both statistical and biological methods to assess the selected drugs. MinDrug is also compared to four state-of-t...