Developed Software/Research Tools

• [Apr/06/2024] Application of Deep Learning for Segmenting Seepages in Levee Systems
• Click here for the data.
  

• IterLUNet: [Sep/15/2022]
• IterLUNet: Deep Learning Architecture for Pixel-Wise Crack Detection in Levee Systems, see Technical Paper: Tech-report (TR-2022/3)

• TAFPred: Backbone [Mar/27/2022]
• TAFPred: Backbone Torsion Angle Fluctuations Prediction from Protein Sequences. See Technical Paper: Tech-report/Preprint
• Click here for the tool (code & data)

• Dispredict3.0 [Mar/12/2022]:
• Dispredict3.0: Prediction of Intrinsically Disordered Proteins with Protein Language Model, see Technical Paper: Tech-report (TR-2022/1)
• Click here for the tool (code & data)
  

• Accurate Gene Regulatory Network (AGRN) [Dec/31/2021]:
• AGRN: Accurate Gene Regulatory Network Inference using Collective Machine Learning Methods
• Click here for the tool (code & data) [Compressed size: 29.3 MB]

 

• Rogue Wave Prediction [Aug/30/2020]:
• An Ensemble-based Prediction of Rogue Waves in Oceanic Waters.
• Click here for the tool [Compressed size: about 8 GB].
  

• PCa-Clf [May/01/2020]:
• A Classifier of Prostate Cancer Patients into Indolent and Aggressive Using Machine Learning.
• Click here for the tool [Compressed size: about 46 MB].
  

• Liz_Tool [Mar/01/2020]
• A Machine-Learning tool to Predict the Multivariate Performance Phenotype Elements.
• Click here for the tool

 

•    ClassifyTE [July/02/2019]
• Machine Learning based Prediction of Hierarchical Classification of Transposable Elements [KDD paper]
• Click here for code and data
  

• diSBPred [July/19/2019]
• A Machine Learning-based Approach for Disulfide Bond Prediction
• Click here for code and data
  

• AIBH [April/27/2019]
• Accurate Identification of Brain Hemorrhage using Genetic Algorithm based Feature Selection and Stacking
• Click here for code and data   
  

 

• StackCBPred [Nov/14/2018]
• A Stacking based Prediction of Protein-Carbohydrate Binding Sites from Sequence (Readme)
• Click here for code and data
  Online server here
• Technical Paper #1, "StackCBPred: A Stacking based Prediction of Protein-Carbohydrate Binding Sites from Sequence," Tech-report (TR-2018/3).

• StackSSSPred [July/01/2018]:
• StackSSSPred: A Stacking based Prediction of Supersecondary Structure from Sequence
• Benchmark data for supersecondary structure prediction only from sequence, is available here.

 

• StackDPPred [Mar/15/2018]
• A Stacking based Prediction of DNA-binding Proteins from Sequences (Readme)
• Click here for code and data
• Online server here
• Technical Paper #1, "StackDPPred: A Stacking based Prediction of DNA-binding Protein from Sequence," Tech-report (TR-2018/2).
  

• PBRpredict-Suite
• A Peptide-Binding Residue Predictor-Suite (Readme)
• Click here for code and data
  

• PBRpredict
• A Peptide-Binding Residue Predictor
• Click here for code and data

BIRpredict

o   Predicts Binding Inducing Regions of Receptor Proteins in a Complex

o   Click here for data.

PCaAnalyser:

o   A 2D-Image Analysis Based Module for Effective Determination of Prostate CancerProgression in 3D Culture (publication)

o   Click here for code and data.

• DisPredict:
• Disorder Protein Predictor. Click here for code and data.
• Tech-report (TR-2014/1), published in PLOS One in 2015.
• CASP11's abstract.

• DisPredict2:
• Disorder Protein Predictor version #2, includes PSEE: Position Specific Estimated Energy.
• Corresponding article, "Estimation of Free Energy Contribution of Protein Residues as Featurefor Structure Prediction from Sequence", is coming soon.
  

• 3DIGARS:
• Energy Function. Click here for code and data.
• Tech-report (TR-2014/2), Accepted in Current Bioinformatics, Bentham Journal in 2015, for publication.
• Update version 2: 3DIGARS-2.0. Click here for code, see: publication.
• Update version 3.0: 3DIGARS-3.0. Click here for code.

• sDFIRE:
• Sequence-specific statistical energy function for protein structure prediction by decoyselections (published)
• Supplementary-material. 
• For the software, DFIRE, dDFIRE and SPINE-X are needed (can be found here: http://sparks-lab.org/index.php/Main/Downloads).

• REGAd³p:
• A real value predictor of Accessible Surface Area (ASA) by Regularized Exact regression, with optimization by Genetic Algorithm and using polynomial kernel of degree 3. (Layman's summary)
• Click here for code and data.
• Tech-report (TR-2015/1), see: publication.

• MetaSSPred:
• A Balanced Secondary Structure Predictor (Layman's summary)
• Click here for code and data.
• Tech-report (TR-2015/2), see publication.

• GAPlus:
• "An Enhanced Genetic Algorithm for Ab initio Protein Structure Prediction," DOI: 10.1109/TEVC.2015.2505317.
• Click here for the code.
• How to Execute.

• MH_GA:
• "Guided macro-mutation in a graded energy based genetic algorithm for protein structureprediction," in Computational Biology and Chemistry, Elsevier (Accepted).
• Click for the code.

• Sampling:
• Article #1: Genetic Algorithm based Improved Sampling for Protein Structure Prediction, Accepted in International Journal of Bio-Inspired Computation, Tech-report (TR-2015/4). Click for the code.
• Article #2: hGRGA: A Scalable Genetic Algorithm using Homologous Gene Schema Replacement,Tech-report (TR-2016/1). Click for the code.
• Article #3: AMLGA: A Genetic Algorithm with Adaptive and Memory-Assisted LocalOperators, Tech-report (TR-2016/2). Click for the code.

• Ab initio Protein Structure Predictor
• Version 1: Click for the code.
• Version 2: Click for the code.
• Technical-Paper #1: 3DIGARS-PSP: A Novel Statistical Energy Function and EffectiveConformational Search Strategy based ab initio Protein Structure Prediction, Tech-report (TR-2018/1).

• Behavior Predictor, DVB
• A Machine Learning Approach to Determine Oyster Vessel Behavior, given tracking data. Click for code and data.

• NASA's Patent Classifier Software, Data is available here
• NASA's Software Category: BaseLine Data
• APAS: APAS_tool
• Catalog SW web with Tag inserted: here
• NASA's Software+Patent Classifier: here, Demo Video is available here,
• NASA Risk Prediction: Final Product,  here
• Other to NMIS here

 

• DataSets
• Angle-fluctuation datasets here.

 

• Detection of rip current from images
• Code
• Dataset
• Large_dataset
• Technical Report: "Machine Learning Applications in Detecting Rip Currents from Images," Tech-report (TR-2018/3).

• Detection of Levee Crack from Images
• Code and Data

• Detection of Sand-Boil
•  Code and Data

• Rogue Wave Detection
• Code