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  Subjects -> ENGINEERING (Total: 2167 journals)
    - CHEMICAL ENGINEERING (185 journals)
    - CIVIL ENGINEERING (168 journals)
    - ELECTRICAL ENGINEERING (91 journals)
    - ENGINEERING (1176 journals)
    - HYDRAULIC ENGINEERING (56 journals)
    - INDUSTRIAL ENGINEERING (54 journals)
    - MECHANICAL ENGINEERING (81 journals)

CHEMICAL ENGINEERING (185 journals)                  1 2     

AATCC Journal of Research     Full-text available via subscription   (Followers: 2)
ACS Combinatorial Science     Full-text available via subscription   (Followers: 10)
Acta Crystallographica Section B: Structural Science, Crystal Engineering and Materials     Hybrid Journal   (Followers: 4)
Acta Polymerica     Hybrid Journal   (Followers: 6)
Additives for Polymers     Full-text available via subscription   (Followers: 21)
Adhesion Adhesives & Sealants     Hybrid Journal   (Followers: 5)
Advanced Chemical Engineering Research     Open Access   (Followers: 9)
Advanced Powder Technology     Hybrid Journal   (Followers: 16)
Advances in Applied Ceramics     Partially Free   (Followers: 3)
Advances in Chemical Engineering     Full-text available via subscription   (Followers: 17)
Advances in Chemical Engineering and Science     Open Access   (Followers: 23)
Advances in Polymer Technology     Hybrid Journal   (Followers: 11)
African Journal of Pure and Applied Chemistry     Open Access   (Followers: 5)
Annual Review of Analytical Chemistry     Full-text available via subscription   (Followers: 9)
Annual Review of Chemical and Biomolecular Engineering     Full-text available via subscription   (Followers: 11)
Anti-Corrosion Methods and Materials     Hybrid Journal   (Followers: 5)
Applied Petrochemical Research     Open Access   (Followers: 3)
Asia-Pacific Journal of Chemical Engineering     Hybrid Journal   (Followers: 6)
Biochemical Engineering Journal     Hybrid Journal   (Followers: 9)
Biomass Conversion and Biorefinery     Partially Free   (Followers: 6)
BMC Chemical Biology     Open Access   (Followers: 4)
Brazilian Journal of Chemical Engineering     Open Access   (Followers: 3)
Bulletin of the Chemical Society of Ethiopia     Open Access   (Followers: 2)
Carbohydrate Polymers     Hybrid Journal   (Followers: 9)
Catalysts     Open Access   (Followers: 7)
Chemical and Engineering News     Free   (Followers: 5)
Chemical and Materials Engineering     Open Access   (Followers: 1)
Chemical and Petroleum Engineering     Hybrid Journal   (Followers: 9)
Chemical and Process Engineering     Open Access   (Followers: 3)
Chemical and Process Engineering Research     Open Access   (Followers: 5)
Chemical Communications     Full-text available via subscription   (Followers: 31)
Chemical Engineering & Technology     Hybrid Journal   (Followers: 24)
Chemical Engineering and Processing: Process Intensification     Hybrid Journal   (Followers: 10)
Chemical Engineering and Science     Open Access   (Followers: 3)
Chemical Engineering Communications     Hybrid Journal   (Followers: 10)
Chemical Engineering Journal     Hybrid Journal   (Followers: 21)
Chemical Engineering Research and Design     Hybrid Journal   (Followers: 17)
Chemical Engineering Research Bulletin     Open Access  
Chemical Engineering Science     Hybrid Journal   (Followers: 13)
Chemical Geology     Hybrid Journal   (Followers: 11)
Chemical Papers     Hybrid Journal   (Followers: 3)
Chemical Product and Process Modeling     Hybrid Journal   (Followers: 3)
Chemical Reviews     Full-text available via subscription   (Followers: 174)
Chemical Society Reviews     Full-text available via subscription   (Followers: 33)
Chemical Technology     Open Access   (Followers: 5)
ChemInform     Hybrid Journal   (Followers: 3)
Chemistry & Industry     Hybrid Journal   (Followers: 2)
Chemistry Central Journal     Open Access   (Followers: 5)
Chemistry of Materials     Full-text available via subscription   (Followers: 140)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 6)
ChemSusChem     Hybrid Journal   (Followers: 8)
Chinese Chemical Letters     Full-text available via subscription   (Followers: 2)
Chinese Journal of Chemical Engineering     Full-text available via subscription   (Followers: 3)
Chinese Journal of Chemical Physics     Hybrid Journal   (Followers: 1)
Coke and Chemistry     Hybrid Journal  
Coloration Technology     Hybrid Journal   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 8)
Computer Aided Chemical Engineering     Full-text available via subscription   (Followers: 2)
Computers & Chemical Engineering     Hybrid Journal   (Followers: 7)
CORROSION     Full-text available via subscription   (Followers: 3)
Corrosion Engineering, Science and Technology     Hybrid Journal   (Followers: 22)
Corrosion Reviews     Hybrid Journal   (Followers: 4)
Crystal Research and Technology     Hybrid Journal   (Followers: 2)
Current Opinion in Chemical Engineering     Open Access   (Followers: 3)
Education for Chemical Engineers     Hybrid Journal   (Followers: 4)
Ekologia : The Journal of Institute of Landscape Ecology of Slovak Academy of Sciences     Open Access  
Eksergi     Open Access  
Emerging Trends in Chemical Engineering     Full-text available via subscription  
European Polymer Journal     Hybrid Journal   (Followers: 41)
Fibers and Polymers     Full-text available via subscription   (Followers: 3)
Fluorescent Materials     Open Access  
Focusing on Modern Food Industry     Open Access   (Followers: 3)
Frontiers of Chemical Science and Engineering     Hybrid Journal   (Followers: 1)
Gels     Open Access  
Geochemistry International     Hybrid Journal  
Handbook of Powder Technology     Full-text available via subscription   (Followers: 3)
Heat Exchangers     Open Access   (Followers: 1)
High Performance Polymers     Hybrid Journal  
Indian Chemical Engineer     Hybrid Journal   (Followers: 3)
Indian Journal of Chemical Technology (IJCT)     Open Access   (Followers: 12)
Industrial & Engineering Chemistry     Full-text available via subscription   (Followers: 9)
Industrial & Engineering Chemistry Research     Full-text available via subscription   (Followers: 20)
Industrial Chemistry Library     Full-text available via subscription   (Followers: 4)
Info Chimie Magazine     Full-text available via subscription   (Followers: 2)
International Journal of Chemical and Petroleum Sciences     Open Access   (Followers: 2)
International Journal of Chemical Engineering     Open Access   (Followers: 7)
International Journal of Chemical Reactor Engineering     Hybrid Journal   (Followers: 3)
International Journal of Chemical Technology     Open Access   (Followers: 4)
International Journal of Chemoinformatics and Chemical Engineering     Full-text available via subscription   (Followers: 2)
International Journal of Food Science     Open Access   (Followers: 3)
International Journal of Industrial Chemistry     Open Access  
International Journal of Polymeric Materials     Hybrid Journal   (Followers: 3)
International Journal of Science and Engineering     Open Access   (Followers: 7)
International Journal of Waste Resources     Open Access   (Followers: 5)
Journal of Chemical Engineering & Process Technology     Open Access   (Followers: 3)
Journal of Applied Crystallography     Hybrid Journal   (Followers: 4)
Journal of Applied Electrochemistry     Hybrid Journal   (Followers: 13)
Journal of Applied Polymer Science     Hybrid Journal   (Followers: 126)
Journal of Biomaterials Science, Polymer Edition     Hybrid Journal   (Followers: 8)
Journal of Bioprocess Engineering and Biorefinery     Full-text available via subscription  

        1 2     

Journal Cover   Computational Biology and Chemistry
  [SJR: 0.688]   [H-I: 43]   [8 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1476-9271
   Published by Elsevier Homepage  [2811 journals]
  • Support vector machine with a Pearson VII function kernel for
           discriminating halophilic and non-halophilic proteins
    • Abstract: Publication date: October 2013
      Source:Computational Biology and Chemistry, Volume 46
      Author(s): Guangya Zhang , Huihua Ge
      Understanding of proteins adaptive to hypersaline environment and identifying them is a challenging task and would help to design stable proteins. Here, we have systematically analyzed the normalized amino acid compositions of 2121 halophilic and 2400 non-halophilic proteins. The results showed that halophilic protein contained more Asp at the expense of Lys, Ile, Cys and Met, fewer small and hydrophobic residues, and showed a large excess of acidic over basic amino acids. Then, we introduce a support vector machine method to discriminate the halophilic and non-halophilic proteins, by using a novel Pearson VII universal function based kernel. In the three validation check methods, it achieved an overall accuracy of 97.7%, 91.7% and 86.9% and outperformed other machine learning algorithms. We also address the influence of protein size on prediction accuracy and found the worse performance for small size proteins might be some significant residues (Cys and Lys) were missing in the proteins.
      Graphical abstract image

      PubDate: 2015-05-21T01:55:43Z
  • PPM-Dom: A novel method for domain position prediction
    • Abstract: Publication date: December 2013
      Source:Computational Biology and Chemistry, Volume 47
      Author(s): Jing Sun , Runyu Jing , Yuelong Wang , Tuanfei Zhu , Menglong Li , Yizhou Li
      Domains are the structural basis of the physiological functions of proteins, and the prediction of which is an advantageous process on the study of protein structure and function. This article proposes a new complete automatic prediction method, PPM-Dom (Domain Position Prediction Method), for predicting the particular positions of domains in a target protein via its atomic coordinate. The presented method integrates complex networks, community division, and fuzzy mean operator (FMO). The whole sequences are divided into potential domain regions by the complex network and community division, and FMO allows the final determination for the domain position. This method will suffice to predict regions that will form a domain structure and those that are unstructured based on completely new atomic coordinate information of the query sequence, and be able to separate different domains in the same query sequence from each other. On evaluating the performance using an independent testing dataset, PPM-Dom reached 91.41% for prediction accuracy, 96.12% for sensitivity and 92.86% for specificity. The tool bag of PPM-Dom is freely available at
      Graphical abstract image

      PubDate: 2015-05-21T01:55:43Z
  • Pharmacoepidemiological characterization of drug-induced adverse reaction
           clusters towards understanding of their mechanisms
    • Abstract: Publication date: June 2014
      Source:Computational Biology and Chemistry, Volume 50
      Author(s): Sayaka Mizutani , Yousuke Noro , Masaaki Kotera , Susumu Goto
      A big challenge in pharmacology is the understanding of the underlying mechanisms that cause drug-induced adverse reactions (ADRs), which are in some cases similar to each other regardless of different drug indications, and are in other cases different regardless of same drug indications. The FDA Adverse Event Reporting System (FAERS) provides a valuable resource for pharmacoepidemiology, the study of the uses and the effects of drugs in large human population. However, FAERS is a spontaneous reporting system that inevitably contains noise that deviates the application of conventional clustering approaches. By performing a biclustering analysis on the FAERS data we identified 163 biclusters of drug-induced adverse reactions, counting for 691ADRs and 240 drugs in total, where the number of ADR occurrences are consistently high across the associated drugs. Medically similar ADRs are derived from several distinct indications for use in the majority (145/163=88%) of the biclusters, which enabled us to interpret the underlying mechanisms that lead to similar ADRs. Furthermore, we compared the biclusters that contain same drugs but different ADRs, finding the cases where the populations of the patients were different in terms of age, sex, and body weight. We applied a biclustering approach to catalogue the relationship between drugs and adverse reactions from a large FAERS data set, and demonstrated a systematic way to uncover the cases different drug administrations resulted in similar adverse reactions, and the same drug can cause different reactions dependent on the patients’ conditions.
      Graphical abstract image Highlights

      PubDate: 2015-05-21T01:55:43Z
  • Exploring the limits of fold discrimination by structural alignment: A
           large scale benchmark using decoys of known fold
    • Abstract: Publication date: June 2011
      Source:Computational Biology and Chemistry, Volume 35, Issue 3
      Author(s): Siv Midtun Hollup , Michael I. Sadowski , Inge Jonassen , William R. Taylor
      Protein structure comparison by pairwise alignment is commonly used to identify highly similar substructures in pairs of proteins and provide a measure of structural similarity based on the size and geometric similarity of the match. These scores are routinely applied in analyses of protein fold space under the assumption that high statistical significance is equivalent to a meaningful relationship, however the truth of this assumption has previously been difficult to test since there is a lack of automated methods which do not rely on the same underlying principles. As a resolution to this we present a method based on the use of topological descriptions of global protein structure, providing an independent means to assess the ability of structural alignment to maintain meaningful structural correspondances on a large scale. Using a large set of decoys of specified global fold we benchmark three widely used methods for structure comparison, SAP, TM-align and DALI, and test the degree to which this assumption is justified for these methods. Application of a topological edit distance measure to provide a scale of the degree of fold change shows that while there is a broad correlation between high structural alignment scores and low edit distances there remain many pairs of highly significant score which differ by core strand swaps and therefore are structurally different on a global level. Possible causes of this problem and its meaning for present assessments of protein fold space are discussed.
      Graphical abstract image Highlights ► Structure alignment methods are used to assign proteins to fold groups. ► The accuracy of this procedure is difficult to test as the definition of folds can be debated. ► By defining folds topologically and building decoys with defined fold the accuracy of fold assignments can be tested. ► Protein structure alignments decoys of different fold can be assigned a high significance, leading to errors in fold classification. ► This observation can be extended to comparisons between decoy models and real protein structures.

      PubDate: 2015-05-21T01:55:43Z
  • On K-peptide length in composition vector phylogeny of prokaryotes
    • Abstract: Publication date: December 2014
      Source:Computational Biology and Chemistry, Volume 53, Part A
      Author(s): Guanghong Zuo , Qiang Li , Bailin Hao
      Using an enlarged alphabet of K-tuples is the way to carry out alignment-free comparison of genomes in the composition vector (CV) approach to prokaryotic phylogeny. We summarize the known aspects concerning the choice of K and examine the results of using CVs with subtraction of a statistical background for K =3–9 and using raw CVs without subtraction for K =1–12. The criterion for evaluation consists in direct comparison with taxonomy. For prokaryotes the best performances are obtained for K =5 and 6 with subtraction and for K =11, 12 or even more without subtraction. In general, CVs with subtractions are slightly better and less CPU consuming, but CVs without subtraction may provide complementary information.

      PubDate: 2015-05-21T01:55:43Z
  • Direct correlation analysis improves fold recognition
    • Abstract: Publication date: 12 October 2011
      Source:Computational Biology and Chemistry, Volume 35, Issue 5
      Author(s): Michael I. Sadowski , Katarzyna Maksimiak , William R. Taylor
      The extraction of correlated mutations through the method of direct information (DI) provides predicted contact residue pairs that can be used to constrain the three dimensional structures of proteins. We apply this method to a large set of decoy protein folds consisting of many thousand well-constructed models, only tens of which have the correct fold. We find that DI is able to greatly improve the ranking of the true (native) fold but others still remain high scoring that would be difficult to discard due to small shifts in the core beta sheets.
      Graphical abstract image Highlights ► The problem of protein prediction from sequence is difficult and incompletely solved. ► We show that a new method based on correlated mutations in a multiple sequence alignment, filtered through a process to extract direct contacts provide powerful constraints on selecting the correct fold in a large number of well constructed decoy models.

      PubDate: 2015-05-21T01:55:43Z
  • Human–chimpanzee alignment: Ortholog exponentials and paralog power
    • Abstract: Publication date: December 2014
      Source:Computational Biology and Chemistry, Volume 53, Part A
      Author(s): Kun Gao , Jonathan Miller
      Genomic subsequences conserved between closely related species such as human and chimpanzee exhibit an exponential length distribution, in contrast to the algebraic length distribution observed for sequences shared between distantly related genomes. We find that the former exponential can be further decomposed into an exponential component primarily composed of orthologous sequences, and a truncated algebraic component primarily composed of paralogous sequences.

      PubDate: 2015-05-21T01:55:43Z
  • Ancestral population genomics using coalescence hidden Markov models and
           heuristic optimisation algorithms
    • Abstract: Publication date: Available online 4 March 2015
      Source:Computational Biology and Chemistry
      Author(s): Jade Cheng , Thomas Mailund
      With full genome data from several closely related species now readily available, we have the ultimate data for demographic inference. Exploiting these full genomes, however, requires models that can explicitly model recombination along alignments of full chromosomal length. Over the last decade a class of models, based on the sequential Markov coalescence model combined with hidden Markov models, has been developed and used to make inference in simple demographic scenarios. To move forward to more complex demographic modelling we need better and more automated ways of specifying these models and efficient optimisation algorithms for inferring the parameters in complex and often high-dimensional models. In this paper we present a framework for building such coalescence hidden Markov models for pairwise alignments and present results for using heuristic optimisation algorithms for parameter estimation. We show that we can build more complex demographic models than our previous frameworks and that we obtain more accurate parameter estimates using heuristic optimisation algorithms than when using our previous gradient based approaches. Our new framework provides a flexible way of constructing coalescence hidden Markov models almost automatically. While estimating parameters in more complex models is still challenging we show that using heuristic optimisation algorithms we still get a fairly good accuracy.

      PubDate: 2015-03-08T19:03:40Z
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