def METHOD_NAME(sequences, pad_length=13):
  """One-hot encoding for sequences with padding."""
  features = list()
  for sequence in sequences:
    one_hot_seq = to_one_hot_array(sequence)
    num_to_pad = pad_length - len(sequence)
    if num_to_pad % 2 == 0:
      one_hot_seq = np.pad(
          one_hot_seq, [(int(num_to_pad / 2), int(num_to_pad / 2)), (0, 0)],
          mode='constant')
    else:
      one_hot_seq = np.pad(
          one_hot_seq, [(int((num_to_pad + 1) / 2), int((num_to_pad - 1) / 2)),
                        (0, 0)],
          mode='constant')
    features.append(one_hot_seq)
  features = np.asarray(features)
  return features